Dividend payout ratio: Difference between revisions

Revision as of 11:18, 9 November 2013

Foundations of statistics is the usual name for the epistemological debate in statistics over how one should conduct inductive inference from data. Among the issues considered in statistical inference are the question of Bayesian inference versus frequentist inference, the distinction between Fisher's "significance testing" and Neyman-Pearson "hypothesis testing", and whether the likelihood principle should be followed. Some of these issues have been debated for up to 200 years without resolution.Template:Sfn

Bandyopadhyay & ForsterTemplate:Sfn describe four statistical paradigms: "(1) classical statistics or error statistics, (ii) Bayesian statistics, (iii) likelihood-based statistics, and (iv) the Akaikean-Information Criterion-based statistics".

Savage's text Foundations of Statistics has been cited over 10000 times on Google Scholar.^[1] It tells the following.

31 year-old Systems Analyst Bud from Deep River, spends time with pursuits for instance r/c cars, property developers new condo in singapore singapore and books. Last month just traveled to Orkhon Valley Cultural Landscape.

Fisher's "significance testing" vs Neyman-Pearson "hypothesis testing"

In the development of classical statistics in the second quarter of the 20th century two competing models of inductive statistical testing were developed.Template:Sfn Template:Sfn Their relative merits were hotly debatedTemplate:Sfn (for over 25 years) until Fisher's death. While a hybrid of the two methods is widely taught and used, the philosophical questions raised in the debate have not been resolved.

Significance testing

Fisher popularized significant testing, primarily in two popular and highly influential books.Template:Sfn Template:Sfn Fisher's writing style in these books was strong on examples and relatively weak on explanations. The books lacked proofs or derivations of significance test statistics (which placed statistical practice in advance of statistical theory). Fisher's more explanatory and philosophical writing was written much later.Template:Sfn There appear to be some differences between his earlier practices and his later opinions.

Fisher was motivated to obtain scientific experimental results without the explicit influence of prior opinion. The significance test is a probabilistic version of Modus tollens, a classic form of deductive inference. The significance test might be simplistically stated, "If the evidence is sufficiently discordant with the hypothesis, reject the hypothesis". In application, a statistic is calculated from the experimental data, a probability of exceeding that statistic is determined and the probability is compared to a threshold. The threshold (the numeric version of "sufficiently discordant") is arbitrary (usually decided by convention). A common application of the method is deciding whether a treatment has a reportable effect based on a comparative experiment. Statistical significance is a measure of probability not practical importance. It can be regarded as a requirement placed on statistical (signal/noise). The method is based on the assumed existence of an imaginary infinite population corresponding to the null hypothesis.

The significance test requires only one hypothesis. The result of the test is to reject the hypothesis (or not), a simple dichotomy. The test does not distinguish between truth of the hypothesis and insufficiency of evidence to disprove it (so it is like a criminal trial in which the defendant is assumed innocent until proven guilty).

Hypothesis testing

Neyman & Pearson collaborated on a different, but related, problem – selecting among competing hypotheses based on the experimental evidence alone. Of their joint papers the most cited was from 1933.Template:Sfn The famous result of that paper is the Neyman-Pearson lemma. The lemma says that a ratio of probabilities is an excellent criterion for selecting a hypothesis (with the threshold for comparison being arbitrary). The paper proved an optimality of Student's t-test (one of the significance tests). Neyman expressed the opinion that hypothesis testing was a generalization of and an improvement on significance testing. The rationale for their methods is found in their joint papers.Template:Sfn

Hypothesis testing requires multiple hypotheses. A hypothesis is always selected, a multiple choice. A lack of evidence is not an immediate consideration. The method is based on the assumption of a repeated sampling of the same population (the classical frequentist assumption).

Grounds of disagreement

The length of the dispute allowed the debate of a wide range of issues regarded as foundational to statistics.

An example exchange from 1955-1956
Fisher's AttackTemplate:Sfn	Neyman's RebuttalTemplate:Sfn	Discussion
Repeated sampling of the same population Such sampling is the basis of frequentist probability Fisher preferred fiducial inference	Fisher's theory of fiducial inference is flawed Paradoxes are common	Fisher's attack on the basis of frequentist probability failed, but was not without result. He identified a specific case (2x2 table) where the two schools of testing reach different results. This case is one of several that are still troubling. Commentators believe that the "right" answer is context dependent.Template:Sfn Fiducial probability has not fared well, being virtually without advocates, while frequentist probability remains a mainstream interpretation.
Type II errors Which result from an alternative hypothesis	A purely probabilistic theory of tests requires an alternative hypothesis	Fisher's attack on type II errors has faded with time. In the intervening years statistics has separated the exploratory from the confirmatory. In the current environment, the concept of type II errors is used in power calculations for confirmatory hypothesis test sample size determination.
Inductive behavior (Vs inductive reasoning, Fisher's preference)		Fisher's attack on inductive behavior has been largely successful because of his selection of the field of battle. While operational decisions are routinely made on a variety of criteria (such as cost), scientific conclusions from experimentation are typically made on the basis of probability alone.

In this exchange Fisher also discussed the requirements for inductive inference, with specific criticism of cost functions penalizing faulty judgments. Neyman countered that Gauss and Laplace used them. This exchange of arguments occurred 15 years after textbooks began teaching a hybrid theory of statistical testing.

Fisher and Neyman were in disagreement about the foundations of statistics (although united in opposition to the Bayesian view):

The interpretation of probability
- The disagreement over Fisher's inductive reasoning vs Neyman's inductive behavior contained elements of the Bayesian/Frequentist divide. Fisher was willing to alter his opinion (reaching a provisional conclusion) on the basis of a calculated probability while Neyman was more willing to change his observable behavior (making a decision) on the basis of a computed cost.
The proper formulation of scientific questions with special concern for modelingTemplate:Sfn Template:Sfn
Whether it is reasonable to reject a hypothesis based on a low probability without knowing the probability of an alternative
Whether a hypothesis could every be accepted on the basis of data
- In mathematics, deduction proves, counter-examples disprove
- In the Popperian philosophy of science, advancements are made when theories are disproven
Subjectivity: While Fisher and Neyman struggled to minimize subjectivity, both acknowledged the importance of "good judgment". Each accused the other of subjectivity.
- Fisher subjectively chose the null hypothesis.
- Neyman-Pearson subjectively chose the criterion for selection (which was not limited to a probability).
- Both subjectively determined numeric thresholds.

Fisher and Neyman were separated by attitudes and perhaps language. Fisher was a scientist and an intuitive mathematician. Inductive reasoning was natural. Neyman was a rigorous mathematician. He was convinced by deductive reasoning rather by a probability calculation based on an experiment.Template:Sfn Thus there was an underlying clash between applied and theoretical, between science and mathematics.

Related history

Neyman, who had occupied the same building in England as Fisher, accepted a position on the west coast of the United States of America in 1938. His move effectively ended his collaboration with Pearson and their development of hypothesis testing.Template:Sfn Further development was continued by others.

Textbooks provided a hybrid version of significance and hypothesis testing by 1940.Template:Sfn None of the principals had any known personal involvement in the further development of the hybrid taught in introductory statistics today.Template:Sfn

Statistics later developed in different directions including decision theory (and possibly game theory), Bayesian statistics, exploratory data analysis, robust statistics and nonparametric statistics. Neyman-Pearson hypothesis testing contributed strongly to decision theory which is very heavily used (in statistical quality control for example). Hypothesis testing readily generalized to accept prior probabilities which gave it a Bayesian flavor. Neyman-Pearson hypothesis testing has become an abstract mathematical subject taught in post-graduate statistics,Template:Sfn while most of what is taught to under-graduates and used under the banner of hypothesis testing is from Fisher.

Contemporary opinion

No major battles between the two classical schools of testing have erupted for decades, but sniping continues (perhaps encouraged by partisans of other controversies). After generations of dispute, there is virtually no chance that either statistical testing theory will replace the other in the foreseeable future.

The hybrid of the two competing schools of testing can be viewed very differently – as the imperfect union of two mathematically complementary ideas Template:Sfn or as the fundamentally flawed union of philosophically incompatible ideas.Template:Sfn Fisher enjoyed some philosophical advantage, while Neyman & Pearson employed the more rigorous mathematics. Hypothesis testing is controversial among some users, but the most popular alternative (confidence intervals) is based on the same mathematics.

The history of the development left testing without a single citable authoritative source for the hybrid theory that reflects common statistical practice. The merged terminology is also somewhat inconsistent. There is strong empirical evidence that the graduates (and instructors) of an introductory statistics class have a weak understanding of the meaning of hypothesis testing.Template:Sfn

Summary

The interpretation of probability has not been resolved (but fiducial probability is an orphan).
Neither test method has been rejected. Both are heavily used for different purposes.
Texts have merged the two test methods under the term hypothesis testing.
- Mathematicians claim that (with some exceptions) that significance tests are a special case of hypothesis tests.
- Others treat the problems and methods as distinct (or incompatible).
The dispute has adversely affected statistical education.

Bayesian inference versus frequentist inference

Two different interpretations of probability (based on objective evidence and subjective degrees of belief) have long existed. Gauss and Laplace could have debated alternatives more than 200 years ago. Two competing schools of statistics have developed as a consequence. Classical inferential statistics was largely developed in the second quarter of the 20th Century,Template:Sfn much of it in reaction to the (Bayesian) probability of the time which utilized the ambiguous principle of indifference to establish prior probabilities. The rehabilitation of Bayesian inference was a reaction to the limitations of frequentist probability. More reactions followed. While the philosophical interpretations are old, the statistical terminology is not. The current statistical terms Bayesian and frequentist were stabilized in the second half of the 20th Century.Template:Sfn The (philosophical, mathematical, scientific, statistical) terminology is confusing: the "classical" interpretation of probability is Bayesian while "classical" statistics is frequentist. "Frequentist" also has varying interpretations - different in philosophy than in physics.

The nuances of philosophical probability interpretations are discussed elsewhere. In statistics the alternative interpretations enable the analysis of different data using different methods based on different models to achieve slightly different goals. Any statistical comparison of the competing schools considers pragmatic criteria beyond philosophical.

Major contributors

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church.

Two major contributors to frequentist (classical) methods were Fisher and Neyman.Template:Sfn Fisher's interpretation of probability was idiosyncratic (but strongly non-Bayesian). Neyman's views were rigorously frequentist. Three major contributors to 20th century Bayesian statistical philosophy, mathematics and methods were de Finetti,Template:Sfn Jeffreys Template:Sfn and Savage.Template:Sfn Savage popularized de Finetti's ideas in the English-speaking world and made Bayesian mathematics rigorous. In 1965, Dennis Lindley's 2-volume work "Introduction to Probability and Statistics from a Bayesian Viewpoint" brought Bayesian methods to a wide audience. Statistics has advanced over the past 3 generations; The "authoritative" views of the early contributors are not all current.

Contrasting approaches

Frequentist inference

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church.

Frequentist inference is partially and tersely described above in (Fisher's "significance testing" vs Neyman-Pearson "hypothesis testing"). Frequentist inference combines several different views. The result is capable of supporting scientific conclusions, making operational decisions and estimating parameters with or without confidence intervals. Frequentist inference is based solely on the (one set of) evidence.

Bayesian inference

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church.

A classical frequency distribution describes the probability of the data. The use of Bayes' theorem allows a more abstract concept – the probability of a hypothesis (corresponding to a theory) given the data. The concept was once known as "inverse probability". Bayesian inference updates the probability estimate for a hypothesis as additional evidence is acquired. Bayesian inference is explicitly based on the evidence and prior opinion, which allows it to be based on multiple sets of evidence.

Comparisons of characteristics

Frequentists and Bayesians use different models of probability. Frequentists often consider parameters to be fixed but unknown while Bayesians assign probability distributions to similar parameters. Consequently Bayesians speak of probabilities that don't exist for frequentists; A Bayesian speaks of the probability of a theory while a true frequentist can speak only of the consistency of the evidence with the theory. Example: A frequentist does not say that there is a 95% probability that the true value of a parameter lies within a confidence interval, saying instead that 95% of confidence intervals contain the true value.

Efron'sTemplate:Sfn comparative adjectives
	Bayes	Frequentist
Basis Resulting Characteristic _ Ideal Application Target Audience Modeling Characteristic	Belief (prior) Principled Philosophy One distribution Dynamic (repeated sampling) Individual (subjective) Aggressive	Behavior (method) Opportunistic Methods Many distributions (bootstrap?) Static (one sample) Community (objective) Defensive

Alternative comparisonTemplate:Sfn Template:Sfn
	Bayesian	Frequentist
Strengths	Complete Coherent Prescriptive _ _ _ _ _ Strong inference from model	Inferences well calibrated No need to specify prior distributions Flexible range of procedures Unbiasness, sufficiency, ancillarity... Widely applicable and dependable Asymptotic theory Easy to interpret Can be calculated by hand Strong model formulation & assessment
Weaknesses	Too subjective for scientific inference Denies the role of randomization for design Requires and relies on full specification of a model (likelihood and prior) _ _ _ Weak model formulation & assessment	Incomplete Ambiguous Incoherent Not prescriptive No unified theory (Over?)emphasis on asymptotic properties Weak inference from model

Mathematical results

Neither school is immune from mathematical criticism and neither accepts it without a struggle. Stein's paradox (for example) illustrated that finding a "flat" or "uninformative" prior probability distribution in high dimensions is subtle.Template:Sfn Bayesians regard that as peripheral to the core of their philosophy while finding frequentism to be riddled with inconsistencies, paradoxes and bad mathematical behavior. Frequentists can explain most. Some of the "bad" examples are extreme situations - such as estimating the weight of a herd of elephants from measuring the weight of one ("Basu's elephants"), which allows no statistical estimate of the variability of weights. The likelihood principle has been a battleground.

Statistical results

Both schools have achieved impressive results in solving real-world problems. Classical statistics effectively has the longer record because numerous results were obtained with mechanical calculators and printed tables of special statistical functions. Bayesian methods have been highly successful in the analysis of information that is naturally sequentially sampled (radar and sonar). Many Bayesian methods and some recent frequentist methods (such as the bootstrap) require the computational power widely available only in the last several decades.

There is hint that Bayesian philosophy is "book smart" compared to Frequentist "street smarts". Bayesian philosophy has sometimes been silent on shuffling the cards. The "design of experiments" teaches the importance of the source of statistical data. Fisher was a major contributor to the theory.

There is active discussion about combining Bayesian and frequentist methods,Template:Sfn Template:Sfn but reservations are expressed about the meaning of the results and reducing the diversity of approaches.

Philosophical results

Baysians are united in opposition to the limitations of frequentism, but are philosophically divided into numerous camps (empirical, hierarchical, objective, personal, subjective), each with a different emphasis. One (frequentist) philosopher of statistics has noted a retreat from the statistical field to philosophical probability interpretations over the last two generations.Template:Sfn There is a perception that successes in Bayesian applications do not justify the supporting philosophy.Template:Sfn Bayesian methods often create useful models that are not used for traditional inference and which owe little to philosophy.Template:Sfn None of the philosophical interpretations of probability (frequentist or Bayesian) appears robust. The frequentist view to too rigid and limiting while the Bayesian view can be simultaneously objective and subjective, etc.

Illustrative quotations

"carefully used, the frequentist approach yields broadly applicable if sometimes clumsy answers"Template:Sfn
"To insist on unbiased [frequentist] techniques may lead to negative (but unbiased) estimates of a variance; the use of p-values in multiple tests may lead to blatant contradictions; conventional 0.95-confidence regions may actually consist of the whole real line. No wonder that mathematicians find it often difficult to believe that conventional statistical methods are a branch of mathematics."Template:Sfn
"Bayesianism is a neat and fully principled philosophy, while frequentism is a grab-bag of opportunistic, individually optimal, methods."Template:Sfn
"in multiparameter problems flat priors can yield very bad answers"Template:Sfn
"[Bayes' rule] says there is a simple, elegant way to combine current information with prior experience in order to state how much is known. It implies that sufficiently good data will bring previously disparate observers to agreement. It makes full use of available information, and it produces decisions having the least possible error rate."Template:Sfn
"Bayesian statistics is about making probability statements, frequentist statistics is about evaluating probability statements."Template:Sfn
"[S]tatisticians are often put in a setting reminiscent of Arrow’s paradox, where we are asked to provide estimates that are informative and unbiased and confidence statements that are correct conditional on the data and also on the underlying true parameter."Template:Sfn (These are conflicting requirements.)
"formal inferential aspects are often a relatively small part of statistical analysis"Template:Sfn
"The two philosophies, Bayesian and frequentist, are more orthogonal than antithetical."Template:Sfn

Summary

Bayesian theory has a mathematical advantage
- Frequentist probability has existence and consistency problems
- But, finding good priors to apply Bayesian theory remains (very?) difficult
Both theories have impressive records of successful application
Neither supporting philosophical interpretation of probability is robust
There is increasing skepticism of the connection between application and philosophy
Some statisticians are recommending active collaboration (beyond a cease fire)

The likelihood principle

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church. Likelihood is a synonym for probability in common usage. In statistics it is reserved for probabilities that fail to meet the frequentist definition. A probability refers to variable data for a fixed hypothesis while a likelihood refers to variable hypotheses for a fixed set of data. Repeated measurements of a fixed length with a ruler generate a set of observations. Each fixed set of observational conditions is associated with a probability distribution and each set of observations can be interpreted as a sample from that distribution – the frequentist view of probability. Alternatively a set of observations may result from sampling any of a number of distributions (each resulting from a set of observational conditions). The probabilistic relationship between a fixed sample and a variable distribution (resulting from a variable hypothesis) is termed likelihood – a Bayesian view of probability. A set of length measurements may imply readings taken by careful, sober, rested, motivated observers in good lighting.

A likelihood is a probability (or not) by another name which exists because of the limited frequentist definition of probability. Likelihood is a concept introduced and advanced by Fisher for more than 40 years (although prior references to the concept exist and Fisher's support was half-hearted).Template:Sfn The concept was accepted and substantially changed by Jeffreys.Template:Sfn In 1962 Birnbaum "proved" the likelihood principle from premises acceptable to most statisticians.Template:Sfn The "proof" has been disputed by statisticians and philosophers. The principle says that all of the information in a sample is contained in the likelihood function, which is accepted as a valid probability distribution by Bayesians (but not by frequentists).

Some (frequentist) significance tests are not consistent with the likelihood principle. Bayesians accept the principle which is consistent with their philosophy (perhaps encouraged by the discomfiture of frequentists). "[T]he likelihood approach is compatible with Bayesian statistical inference in the sense that the posterior Bayes distribution for a parameter is, by Bayes’s Theorem, found by multiplying the prior distribution by the likelihood function."Template:Sfn Frequentists interpret the principle adversely to Bayesians as implying no concern about the reliability of evidence. "The likelihood principle of Bayesian statistics implies that information about the experimental design from which evidence is collected does not enter into the statistical analysis of the data."Template:Sfn Many Bayesians (Savage for example)Template:Sfn recognize that implication as a vulnerability.

The likelihood principle has become an embarrassment to both major philosophical schools of statistics; It has weakened both rather than favoring either. Its strongest supporters claim that it offers a better foundation for statistics than either of the two schools. "[L]ikelihood looks very good indeed when it is compared with these [Bayesian and frequentist] alternatives."Template:Sfn These supporters include statisticians and philosophers of science.Template:Sfn The concept needs further development before it can be regarded as a serious challenge to either existing school, but it seems to offer a promising compromise position. While Bayesians acknowledge the importance of likelihood for calculation, they believe that the posterior probability distribution is the proper basis for inference.Template:Sfn

Modeling

Mining Engineer (Excluding Oil ) Truman from Alma, loves to spend time knotting, largest property developers in singapore developers in singapore and stamp collecting. Recently had a family visit to Urnes Stave Church. Inferential statistics is based on models. Much of classical hypothesis testing, for example, was based on the assumed normality of the data. Robust and nonparametric statistics were developed to reduce the dependence on that assumption. Bayesian statistics interprets new observations from the perspective of prior knowledge – assuming a modeled continuity between past and present. The design of experiments assumes some knowledge of those factors to be controlled, varied, randomized and observed. Statisticians are well aware of the difficulties in proving causation (more of a modeling limitation than a mathematical one), saying "correlation does not imply causation".

More complex statistics utilizes more complex models, often with the intent of finding a latent structure underlying a set of variables. As models and data sets have grown in complexity,^[2]^[3] foundational questions have been raised about the justification of the models and the validity of inferences drawn from them. The range of conflicting opinion expressed about modeling is large.

Models can be based on scientific theory or on ad-hoc data analysis. The approaches use different methods. There are advocates of each.Template:Sfn
Model complexity is a compromise. The Akaikean information criterion and Bayesian information criterion are two less subjective approaches to achieving that compromise.Template:Sfn
Fundamental reservations have been expressed about even simple regression models used in the social sciences. A long list of assumptions inherent to the validity of a model is typically neither mentioned nor checked. A favorable comparison between observations and model is often considered sufficient.Template:Sfn
Bayesian statistics focuses so tightly on the posterior probability that it ignores the fundamental comparison of observations and model.Template:Sfn
Traditional observation-based models are inadequate to solve many important problems. A much wider range of models, including algorithmic models, must be utilized. "If the model is a poor emulation of nature, the conclusions may be wrong."Template:Sfn
Modeling is often poorly done (the wrong methods are used) and poorly reported.Template:Sfn

In the absence of a strong philosophical consensus review of statistical modeling, many statisticians accept the cautionary words of statistician George Box, "[A]ll models are wrong, but some are useful." (wikiquote)

Notes

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

References

20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
Stuart A., Ord J.K. (1994). Kendall's Advanced Theory of Statistics, volume I: Distribution Theory (Edward Arnold).

One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 The text is a collection of essays.
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
Template:Cite web University of Houston lecture notes?
Template:Cite web Proceedings of the Statistical Problems in Particle Physics, Astrophysics and Cosmology
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 Translation of the 1937 French original with later notes added.
Template:Cite web Preliminary version of an article for the International Encyclopedia of the Social and Behavioral Sciences.
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang A joke escalated into a serious discussion of Bayesian problems by 5 authors (Gelman, Bernardo, Kadane, Senn, Wasserman) on pages 445-478.
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
Template:Cite web A working paper that explains the difference between Fisher's evidential p-value and the Neyman–Pearson Type I error rate $\alpha$ .
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
Template:Cite web
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
Template:Cite web Working paper contains numerous quotations from the original sources of the dispute.
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
One of the biggest reasons investing in a Singapore new launch is an effective things is as a result of it is doable to be lent massive quantities of money at very low interest rates that you should utilize to purchase it. Then, if property values continue to go up, then you'll get a really high return on funding (ROI). Simply make sure you purchase one of the higher properties, reminiscent of the ones at Fernvale the Riverbank or any Singapore landed property Get Earnings by means of Renting

In its statement, the singapore property listing - website link, government claimed that the majority citizens buying their first residence won't be hurt by the new measures. Some concessions can even be prolonged to chose teams of consumers, similar to married couples with a minimum of one Singaporean partner who are purchasing their second property so long as they intend to promote their first residential property. Lower the LTV limit on housing loans granted by monetary establishments regulated by MAS from 70% to 60% for property purchasers who are individuals with a number of outstanding housing loans on the time of the brand new housing purchase. Singapore Property Measures - 30 August 2010 The most popular seek for the number of bedrooms in Singapore is 4, followed by 2 and three. Lush Acres EC @ Sengkang

Discover out more about real estate funding in the area, together with info on international funding incentives and property possession. Many Singaporeans have been investing in property across the causeway in recent years, attracted by comparatively low prices. However, those who need to exit their investments quickly are likely to face significant challenges when trying to sell their property – and could finally be stuck with a property they can't sell. Career improvement programmes, in-house valuation, auctions and administrative help, venture advertising and marketing, skilled talks and traisning are continuously planned for the sales associates to help them obtain better outcomes for his or her shoppers while at Knight Frank Singapore. No change Present Rules

Extending the tax exemption would help. The exemption, which may be as a lot as $2 million per family, covers individuals who negotiate a principal reduction on their existing mortgage, sell their house short (i.e., for lower than the excellent loans), or take part in a foreclosure course of. An extension of theexemption would seem like a common-sense means to assist stabilize the housing market, but the political turmoil around the fiscal-cliff negotiations means widespread sense could not win out. Home Minority Chief Nancy Pelosi (D-Calif.) believes that the mortgage relief provision will be on the table during the grand-cut price talks, in response to communications director Nadeam Elshami. Buying or promoting of blue mild bulbs is unlawful.

A vendor's stamp duty has been launched on industrial property for the primary time, at rates ranging from 5 per cent to 15 per cent. The Authorities might be trying to reassure the market that they aren't in opposition to foreigners and PRs investing in Singapore's property market. They imposed these measures because of extenuating components available in the market." The sale of new dual-key EC models will even be restricted to multi-generational households only. The models have two separate entrances, permitting grandparents, for example, to dwell separately. The vendor's stamp obligation takes effect right this moment and applies to industrial property and plots which might be offered inside three years of the date of buy. JLL named Best Performing Property Brand for second year running

The data offered is for normal info purposes only and isn't supposed to be personalised investment or monetary advice. Motley Fool Singapore contributor Stanley Lim would not personal shares in any corporations talked about. Singapore private home costs increased by 1.eight% within the fourth quarter of 2012, up from 0.6% within the earlier quarter. Resale prices of government-built HDB residences which are usually bought by Singaporeans, elevated by 2.5%, quarter on quarter, the quickest acquire in five quarters. And industrial property, prices are actually double the levels of three years ago. No withholding tax in the event you sell your property. All your local information regarding vital HDB policies, condominium launches, land growth, commercial property and more

There are various methods to go about discovering the precise property. Some local newspapers (together with the Straits Instances ) have categorised property sections and many local property brokers have websites. Now there are some specifics to consider when buying a 'new launch' rental. Intended use of the unit Every sale begins with 10 p.c low cost for finish of season sale; changes to 20 % discount storewide; follows by additional reduction of fiftyand ends with last discount of 70 % or extra. Typically there is even a warehouse sale or transferring out sale with huge mark-down of costs for stock clearance. Deborah Regulation from Expat Realtor shares her property market update, plus prime rental residences and houses at the moment available to lease Esparina EC @ Sengkang
20 year-old Real Estate Agent Rusty from Saint-Paul, has hobbies and interests which includes monopoly, property developers in singapore and poker. Will soon undertake a contiki trip that may include going to the Lower Valley of the Omo.

My blog: http://www.primaboinca.com/view_profile.php?userid=5889534 "Principal components is an empirical approach while factor analysis and structural equation modeling tend to be theoretical approaches." p 27
Template:Cite web Lecture notes? University of Illinois at Chicago

External links

Citations of Savage (1972) at Google Scholar. [Over 10000 citations.]
Stanford Encyclopedia of Philosophy entry on probability interpretations.

↑ Citations of Savage (1972)
↑ Some large models attempt to predict the behavior of voters in the United States of America. The population is around 300 million. Each voter may be influenced by many factors. For some of the complications of voter behavior (most easily understood by the natives) see: http://www.stat.columbia.edu/~gelman/presentations/redbluetalkubc.pdf
↑ Efron mentions millions of data points and thousands of parameters from scientific studies.

[1] Citations of Savage (1972)

[2] Some large models attempt to predict the behavior of voters in the United States of America. The population is around 300 million. Each voter may be influenced by many factors. For some of the complications of voter behavior (most easily understood by the natives) see: http://www.stat.columbia.edu/~gelman/presentations/redbluetalkubc.pdf

[3] Efron mentions millions of data points and thousands of parameters from scientific studies.

[1]

[2]

[3]

Dividend payout ratio: Difference between revisions

Revision as of 11:18, 9 November 2013

Contents

Fisher's "significance testing" vs Neyman-Pearson "hypothesis testing"

Significance testing

Hypothesis testing

Grounds of disagreement

Related history

Contemporary opinion

Summary

Bayesian inference versus frequentist inference

Major contributors

Contrasting approaches

Frequentist inference

Bayesian inference

Comparisons of characteristics

Mathematical results

Statistical results

Philosophical results

Illustrative quotations

Summary

The likelihood principle

Modeling

Other reading

See also

Notes

References

Further reading

External links

Navigation menu

@@ Line 1: / Line 1: @@
-Ɗiet is actսally a basic mɑtter in everyone's daily life. Еveryone has it. We can ɗecide to take in nutritiously, or otherwisе. Don't get worried--it's certаinly easy to commence following healthier eating roսtine no mаtter wҺere you're beginning with, and you can accomplish it without or with salad!<br><br>Lots of people do not hаve ample healthy proteins within their diet plan in spite of how significant it is to good well being. Among the finest causes օf proteins are slim red meat, for example steak. Pork and chicҡen are good healthy proteins resources as wеll. [http://search.un.org/search?ie=utf8&site=un_org&output=xml_no_dtd&client=UN_Website_en&num=10&lr=lang_en&proxystylesheet=UN_Website_en&oe=utf8&q=Protein&Submit=Go Protein] is essential to great muscle improvement.<br><br>To have your self prepareԀ during the day, attempt ɗeveloping a pan of oat meal. Oatmeal iѕ great for trying to keep you total for a long period after you have completeԀ consuming.<br><br>In the event you dine out, consider splitting a meal with a perѕon. Even normal entrees that aren't that large include an excessive amount of meals οften, and therefore could add lots of body fat and caloriе consumption in your diet program. If you ѕplit your dinner, you saѵe yourself caѕh and calorіes. Doing this means you can dine out with out ruining your daily dіet prеpare.<br><br>Eаt a lot of broccoli! This food items offers you a whole amount of nutritional K and vit c. In addition to, broccoli is incredibly full of vit c. You can assist your bones ǥet strong and maybe trim down the likelihood of particular cancer. To remoνe the vегy beѕt level of diet from your broccoli, it must be prepared in the steamer as opposed tо the mіcrowave oven or boiling hot.<br><br>If you аre seaгching for the whօlеsome diet program to սse, make sure that they have youг morning mеal incorporated. Breakfast definitely is reցarded aѕ the critical meal, since it jump starts үour metabolic procеsѕ and flooding your body with essential vitamins and mineralѕ soon after time of not eаting.<br><br>Thе extra virgin olive oil present in most pantries is ɑ good adԀition to healthy skin сare workouts if dryneѕs is a problem you encounter. Olive oil will help gеntlу close off in impoгtant moiѕture in your fingers and face. It also will provide you with herbal antioxiԁants to combat from getting ߋlder pores and skin. An extremely slender covering 2 instancеs per day іs good.<br><br>Peanuts might be a great ԁiet foods. Natural walnuts are loaded with fiber and might also fulfill you when you are craving some thіng crispy.<br><br>Missing youг morning meal may be unfavorable in yοur well being. Occаsionally folks believe they can eliminate some caloriе consumption by skipping breakfast time. In faсt once you ignore morning meal, you will probably turn out to be eхceedіnglү hungrʏ and grab an unhealthy snack foоd afterwards within the time. Without tҺe need of breakfast time along with copious eating, your fіnal caloric full during thе day could end up higher.<br><br>Getting these [https://www.vocabulary.com/dictionary/quality+recipes quality recipes] readily аccessible may help you stay focused on healthful eatіng. Usіng a excеllent selection within your food choices will keep you from getting sick of yoսr diet program.<br><br>To get well quicker аfter simрly being ill, eat  [http://Omkolo.xon.pl/projekt2/userinfo.php?uid=117557 vigrx plus Indonesia Kaskus] something with good levels of zinc. Zinc helps ƴou feel good faster by bolstering your immunity mechanism, along with helping үou prevent upcoming sickness. You can find zinc in strawberries, peaches, pumpkin plant seeds and wheat. The majօrity of these food items have antiоxidants.<br><br>It's wise to not focus on dеliсacy too much. Makе delicacy an exclusive deal with that you jսst have only a period or two every week.<br><br>Make it the goal to ƅakе most of your fooԁ products instead of frying. Foods whiсh cɑn be cooked are decrease іn unhealthy calories and better for you tҺan their fried coսnteгparts. Yօu will see that yoս aгe far more livelү when you try to eat only a healthy diet cooked food products.<br><br>Sugary carrots are an excellent convenience meals but consist of less carЬs than other sorts of cагrots. Swаp mashed potatoes or fries wіth ѕugaгy potatoes. They may be dished up աith butter or even a very little ѕugar. They are able to even enable you to fеel much bеtter should you suffer from rheumatoid arthritis, because tҺey have an anti--inflamed professional.<br><br>Αn excellent meal of fowl, corn, and legumеs is ideal. Yοս ѡіll definitely get a gooɗ harmony of аmino acids while also getting the quantity of ѕtarch that your system needs for the wеll balanced diet. Thiѕ dish іsn't particularly fantaѕtic in rеlation to micronutrients, but in generɑl, it really is a rather wholesome meal. These food items ρyramids are out-of-date and while thеy're not improper, they deficiency numeгous latest wholesome breakthroughs.<br><br>Natural foods which are not remarkably refined generally are filled with diet. Junk foߋds will enhance the excess fаt information in yoսr body. You need to have some concentrate on ingesting just low fat meats and refreshing produce. In the event you have trouble with getting the processed food in a fοod ѕtore, try tߋ avoid tɦe isles that will tempt you.<br><br>Don't neglect cheat dayѕ. Unfaithful signifies you will enjoy a number ߋf anything, but not every օne of anything. On youг own сheat day, limit tҺe sіze of pߋrtions to maintain you from putting on weight.<br><br>Be sure you make easƴ, wholesome, delіghtful fߋods to your familƴ members. When there are simple and easy уummy meals accessible, your loved ones is more likely to consume them. It is vital tօ understand tҺat mealѕ is only aѕ nourishing as the amount of intake. Ƴօu need to make sure the healthіer selections you determine looking at your loved ones can alsօ be delightful selections.<br><br>Self-deprivation is a thing that handful ߋf individuals apprеciate. Nourishment [http://newsadmin.Fusionforge.Shizzlaz.eu/index.php?mod=users&action=view&id=29878 vigrx plus does it work yahoo] not necessarily mean you must deny your self it really signifies you should try to eat a lot more much healtҺier foods and fewer terrible mеаls. This post should have launched your eyеs to  [http://Neytec24.de/pro/Tauschboerse/auktion/item.php?id=3569&mode=1 Rate vigrx plus] the simple actions you can take into the realm of nutrіents.
+'''Foundations of statistics''' is the usual name for the [[epistemology|epistemological]] debate in [[statistics]] over how one should conduct [[inductive inference]] from data.  Among the issues considered in [[statistical inference]] are the question of [[Bayesian inference]] versus [[frequentist inference]], the distinction between [[Ronald Fisher|Fisher]]'s "significance testing" and [[Jerzy Neyman|Neyman]]-[[Egon Pearson|Pearson]] "hypothesis testing", and whether the [[likelihood principle]] should be followed.  Some of these issues have been debated for up to 200 years without resolution.{{sfn|Efron|1978}}
+Bandyopadhyay & Forster{{sfn|Bandyopadhyah & Forster|2011}} describe four statistical paradigms: "(1) classical statistics or error statistics, (ii) Bayesian statistics, (iii) likelihood-based statistics, and (iv) the [[Akaike information criterion|Akaikean-Information Criterion]]-based statistics".
+Savage's text ''Foundations of Statistics'' has been cited over 10000 times on [[Google Scholar]].<ref>[http://scholar.google.co.uk/scholar?cites=9531312933296806388 Citations of Savage (1972)]</ref>  It tells the following.
+{{quote|It is unanimously agreed that statistics depends somehow on probability.  But, as to what probability is and how it is connected with statistics, there has seldom been such complete disagreement and breakdown of communication since the Tower of Babel. Doubtless, much of the disagreement is merely terminological and would disappear under sufficiently sharp analysis.}}
+==Fisher's "significance testing" vs Neyman-Pearson "hypothesis testing"==
+In the development of classical statistics in the second quarter of the 20th
+century two competing models of inductive statistical testing were
+developed.{{sfn|Lehmann|2011}}{{sfn|Gigerenzer|1989}}  Their relative merits were
+hotly debated{{sfn|Louçã|1993}} (for over 25 years) until Fisher's death.  While
+a hybrid of the two methods is widely taught and used, the philosophical
+questions raised in the debate have not been resolved.
+===Significance testing===
+[[Ronald Fisher|Fisher]] popularized significant testing, primarily in two
+popular and highly influential books.{{sfn|Fisher|1925}}{{sfn|Fisher|1935}}
+Fisher's writing style in these books was strong on examples and relatively weak
+on explanations.  The books lacked proofs or derivations of significance test
+statistics (which placed statistical practice in advance of statistical theory).
+Fisher's more explanatory and philosophical writing was written much
+later.{{sfn|Fisher|1956}}  There appear to be some differences between his
+earlier practices and his later opinions.
+Fisher was motivated to obtain scientific experimental results without the
+explicit influence of prior opinion.  The significance test is a
+probabilistic version of [[Modus tollens]], a classic form of deductive
+inference.  The significance test might be simplistically stated, "If the
+evidence is sufficiently discordant with the hypothesis, reject the hypothesis".  In
+application, a statistic is calculated from the experimental data, a probability
+of exceeding that statistic is determined and the probability is compared to a
+threshold.  The threshold (the numeric version of "sufficiently discordant") is
+arbitrary (usually decided by convention).  A common application of the method
+is deciding whether a treatment has a reportable effect based on a comparative
+experiment.  Statistical significance is a measure of probability not practical
+importance.  It can be regarded as a requirement placed on statistical
+(signal/noise).  The method is based on the assumed existence of an imaginary
+infinite population corresponding to the null hypothesis.
+The significance test requires only one hypothesis.  The result of the test is
+to reject the hypothesis (or not), a simple dichotomy.  The test does not
+distinguish between truth of the hypothesis and insufficiency of evidence to
+disprove it (so it is like a criminal trial in which the defendant is assumed innocent until proven guilty).
+===Hypothesis testing===
+[[Jerzy Neyman|Neyman]] & [[Egon Pearson|Pearson]] collaborated on a different,
+but related, problem – selecting among competing hypotheses based on the
+experimental evidence alone.  Of their joint papers the most cited was from
+.{{sfn|Neyman & Pearson|1933}}  The famous result of that paper is the
+[[Neyman-Pearson lemma]].  The lemma says that a ratio of probabilities is an
+excellent criterion for selecting a hypothesis (with the threshold for
+comparison being arbitrary).  The paper proved an optimality of Student's t-test
+(one of the significance tests).  Neyman expressed the opinion that hypothesis
+testing was a generalization of and an improvement on significance testing.  The
+rationale for their methods is found in their joint papers.{{sfn|
+Neyman & Pearson|1967}}
+Hypothesis testing requires multiple hypotheses.  A hypothesis is always
+selected, a multiple choice.  A lack of evidence is not an immediate
+consideration.  The method is based on the assumption of a repeated sampling of
+the same population (the classical frequentist assumption).
+===Grounds of disagreement===
+The length of the dispute allowed the debate of a wide range of issues regarded
+as foundational to statistics.
+{| style="border: 1px solid darkgray;"
+|+ An example exchange from 1955-1956
+! scope="col" | Fisher's Attack{{sfn|Fisher|1955}}
+! scope="col" | Neyman's Rebuttal{{sfn|Neyman|1956}}
+! scope="col" | Discussion
+|-
+| Repeated sampling of the same population
+* Such sampling is the basis of frequentist probability
+* Fisher preferred [[fiducial inference]]
+| Fisher's theory of fiducial inference is flawed
+* Paradoxes are common
+| Fisher's attack on the basis of frequentist probability failed, but was not without result.  He identified a specific case (2x2 table) where the two schools of testing reach different results.  This case is one of several that are still troubling.  Commentators believe that the "right" answer is context dependent.{{sfn|Lehmann|1993}}  Fiducial probability has not fared well, being virtually without advocates, while frequentist probability remains a mainstream interpretation.
+|-
+| Type II errors
+* Which result from an alternative hypothesis
+| A purely probabilistic theory of tests requires an alternative hypothesis
+| Fisher's attack on type II errors has faded with time.  In the intervening years statistics has separated the exploratory from the confirmatory.  In the current environment, the concept of type II errors is used in power calculations for confirmatory hypothesis test [[sample size determination]].
+|-
+| Inductive behavior
+* (Vs [[inductive reasoning]], Fisher's preference)
+|
+| Fisher's attack on inductive behavior has been largely successful because of his selection of the field of battle.  While ''operational decisions'' are routinely made on a variety of criteria (such as cost), ''scientific conclusions'' from experimentation are typically made on the basis of probability alone.
+|}
+In this exchange Fisher also discussed the requirements for inductive inference,
+with specific criticism of cost functions penalizing faulty judgments.  Neyman
+countered that Gauss and Laplace used them.  This exchange of arguments occurred
+years ''after'' textbooks began teaching a hybrid theory of statistical
+testing.
+Fisher and Neyman were in disagreement about the foundations of statistics (although united in opposition to the Bayesian view):
+* The interpretation of probability
+** The disagreement over Fisher's inductive reasoning vs Neyman's inductive behavior contained elements of the Bayesian/Frequentist divide.  Fisher was willing to alter his opinion (reaching a provisional conclusion) on the basis of a calculated probability while Neyman was more willing to change his observable behavior (making a decision) on the basis of a computed cost.
+* The proper formulation of scientific questions with special concern for modeling{{sfn|Louçã|1993}}{{sfn|Lenhard|2006}}
+* Whether it is reasonable to reject a hypothesis based on a low probability without knowing the probability of an alternative
+* Whether a hypothesis could every be accepted on the basis of data
+** In mathematics, deduction proves, counter-examples disprove
+** In the Popperian philosophy of science, advancements are made when theories are disproven
+* Subjectivity: While Fisher and Neyman struggled to minimize subjectivity, both acknowledged the importance of "good judgment".  Each accused the other of subjectivity.
+** Fisher ''subjectively'' chose the null hypothesis.
+** Neyman-Pearson ''subjectively'' chose the criterion for selection (which was not limited to a probability).
+** Both ''subjectively'' determined numeric thresholds.
+Fisher and Neyman were separated by attitudes and perhaps language.  Fisher
+was a scientist and an intuitive mathematician.  Inductive reasoning was
+natural.  Neyman was a rigorous mathematician.  He was convinced by deductive
+reasoning rather by a probability calculation based on an experiment.{{sfn
+|Lehmann|2011}}  Thus there was an underlying clash between applied and
+theoretical, between science and mathematics.
+===Related history===
+Neyman, who had occupied the same building in England as Fisher, accepted a
+position on the west coast of the United States of America in 1938.  His move
+effectively ended his collaboration with Pearson and their development of
+hypothesis testing.{{sfn|Lehmann|2011}}  Further development was continued by
+others.
+Textbooks provided a hybrid version of significance and hypothesis testing by
+.{{sfn|Halpin|2006}}  None of the principals had any known personal
+involvement in the further development of the hybrid taught in introductory
+statistics today.{{sfn|Gigerenzer|1989}}
+Statistics later developed in different directions including decision theory
+(and possibly game theory), Bayesian statistics, exploratory data analysis,
+robust statistics and nonparametric statistics.  Neyman-Pearson hypothesis
+testing contributed strongly to decision theory which is very heavily used (in
+statistical quality control for example).  Hypothesis testing readily
+generalized to accept prior probabilities which gave it a Bayesian flavor.
+Neyman-Pearson hypothesis testing has become an abstract mathematical subject
+taught in post-graduate statistics,{{sfn|Lehmann & Romano|2005}} while most of
+what is taught to under-graduates and used under the banner of hypothesis
+testing is from Fisher.
+===Contemporary opinion===
+No major battles between the two classical schools of testing have erupted for
+decades, but sniping continues (perhaps encouraged by partisans of other
+controversies).  After generations of dispute, there is virtually no chance that
+either statistical testing theory will replace the other in the foreseeable
+future.
+The hybrid of the two competing schools of testing can be viewed very
+differently – as the imperfect union of two mathematically complementary ideas
+{{sfn|Lehmann|1993}} or as the fundamentally flawed union of philosophically
+incompatible ideas.{{sfn|Hubbard & Bayarri|2003?}}  Fisher enjoyed some
+philosophical advantage, while Neyman & Pearson employed the more rigorous
+mathematics.  Hypothesis testing is
+[[Statistical hypothesis testing#Criticism|controversial]] among some users, but
+the most popular alternative (confidence intervals) is based on the same
+mathematics.
+The history of the development left testing without a single citable
+authoritative source for the hybrid theory that reflects common statistical
+practice.  The merged terminology is also somewhat inconsistent.  There is
+strong empirical evidence that the graduates (and instructors) of an
+introductory statistics class have a weak understanding of the meaning of
+hypothesis testing.{{sfn|Sotos|2007}}
+===Summary===
+* The interpretation of probability has not been resolved (but fiducial probability is an orphan).
+* Neither test method has been rejected.  Both are heavily used for different purposes.
+* Texts have merged the two test methods under the term hypothesis testing.
+** Mathematicians claim that (with some exceptions) that significance tests are a special case of hypothesis tests.
+** Others treat the problems and methods as distinct (or incompatible).
+* The dispute has adversely affected statistical education.
+==Bayesian inference versus frequentist inference==
+Two different interpretations of probability (based on objective evidence and
+subjective degrees of belief) have long existed.  Gauss and
+Laplace could have debated alternatives more than 200 years ago.  Two competing
+schools of statistics have developed as a consequence.
+Classical inferential statistics was largely developed in the second quarter of
+the 20th Century,{{sfn|Gigerenzer|1989}} much of it in reaction to the
+(Bayesian) probability of the time which utilized the ambiguous
+[[principle of indifference]] to establish prior probabilities.  The
+rehabilitation of Bayesian inference was a reaction to the limitations of
+frequentist probability.  More reactions followed.  While the philosophical interpretations are old, the statistical
+terminology is not.  The current statistical terms Bayesian and frequentist
+were stabilized in the second half of the 20th Century.{{sfn|Fienberg|2006}}
+The (philosophical, mathematical, scientific, statistical) terminology is
+confusing: the "classical" interpretation of probability is Bayesian while
+"classical" statistics is frequentist.  "Frequentist" also has varying
+interpretations - different in philosophy than in physics.
+The nuances of philosophical [[probability interpretations]] are discussed
+elsewhere.  In statistics the alternative interpretations ''enable'' the
+analysis of different data using different methods based on different models to
+achieve slightly different goals.  Any statistical comparison of the competing
+schools considers pragmatic criteria beyond philosophical.
+===Major contributors===
+{{main|History of statistics}}
+Two major contributors to frequentist (classical) methods were
+[[Ronald Fisher|Fisher]] and [[Jerzy Neyman|Neyman]].{{sfn|Lehmann|2011}}
+Fisher's interpretation of probability was idiosyncratic (but strongly
+non-Bayesian).  Neyman's views were rigorously frequentist.  Three major
+contributors to 20th century Bayesian statistical philosophy, mathematics and
+methods were [[Bruno de Finetti|de Finetti]],{{sfn|de Finetti|1964}}
+[[Harold Jeffreys|Jeffreys]]{{sfn|Jeffreys|1939}} and
+[[Leonard Jimmie Savage|Savage]].{{sfn|Savage|1954}}  Savage popularized
+de Finetti's ideas in the English-speaking world and made Bayesian mathematics
+rigorous.   In 1965, Dennis Lindley's 2-volume work "Introduction to Probability
+and Statistics from a Bayesian Viewpoint" brought Bayesian methods to a wide
+audience.  Statistics has advanced over the past 3 generations; The
+"authoritative" views of the early contributors are not all current.
+===Contrasting approaches===
+====Frequentist inference====
+{{main|Frequentist inference}}
+Frequentist inference is partially and tersely described above in (Fisher's
+"significance testing" vs Neyman-Pearson "hypothesis testing").  Frequentist
+inference combines several different views.  The result is capable of supporting
+scientific conclusions, making operational decisions and estimating parameters
+with or without [[confidence intervals]].  Frequentist inference is based solely
+on the (one set of) evidence.
+====Bayesian inference====
+{{main|Bayesian inference}}
+A classical frequency distribution describes the probability of the data.  The
+use of [[Bayes' theorem]] allows a more abstract concept – the probability of
+a hypothesis (corresponding to a theory) given the data.  The concept was once
+known as "inverse probability".  Bayesian inference updates the probability
+estimate for a hypothesis as additional evidence is acquired.  Bayesian
+inference is explicitly based on the evidence and prior opinion, which allows it
+to be based on multiple sets of evidence.
+====Comparisons of characteristics====
+Frequentists and Bayesians use different models of probability.  Frequentists
+often consider parameters to be fixed but unknown while Bayesians assign
+probability distributions to similar parameters.  Consequently Bayesians speak
+of probabilities that don't exist for frequentists; A Bayesian speaks of the
+probability of a theory while a true frequentist can speak only of the
+consistency of the evidence with the theory.  Example: A frequentist does not
+say that there is a 95% probability that the true value of a parameter lies
+within a confidence interval, saying instead that 95% of confidence intervals
+contain the true value.
+{| style="border: 1px solid darkgray;"
+|+ Efron's{{sfn|Efron|2013}} comparative adjectives
+! scope="col" |
+! scope="col" | Bayes
+! scope="col" | Frequentist
+|-
+|
+*Basis
+*Resulting Characteristic
+*_
+*Ideal Application
+*Target Audience
+*Modeling Characteristic
+|
+*Belief (prior)
+*Principled Philosophy
+*One distribution
+*Dynamic (repeated sampling)
+*Individual (subjective)
+*Aggressive
+|
+*Behavior (method)
+*Opportunistic Methods
+*Many distributions (bootstrap?)
+*Static (one sample)
+*Community (objective)
+*Defensive
+|}
+{| style="border: 1px solid darkgray;"
+|+ Alternative comparison{{sfn|Little|2005}}{{sfn|Yu|2009}}
+! scope="col" |
+! scope="col" | Bayesian
+! scope="col" | Frequentist
+|-
+|
+ Strengths
+|
+*Complete
+*Coherent
+*Prescriptive
+*_
+*_
+*_
+*_
+*_
+*Strong inference from model
+|
+*Inferences well calibrated
+*No need to specify prior distributions
+*Flexible range of procedures
+**Unbiasness, sufficiency, ancillarity...
+**Widely applicable and dependable
+**Asymptotic theory
+**Easy to interpret
+**Can be calculated by hand
+*Strong model formulation & assessment
+|-
+|
+ Weaknesses
+|
+*Too subjective for scientific inference
+*Denies the role of randomization for design
+*Requires and relies on full specification of a model (likelihood and prior)
+*_
+*_
+*_
+*Weak model formulation & assessment
+|
+*Incomplete
+*Ambiguous
+*Incoherent
+*Not prescriptive
+*No unified theory
+*(Over?)emphasis on asymptotic properties
+*Weak inference from model
+|}
+===Mathematical results===
+Neither school is immune from mathematical criticism and neither accepts it
+without a struggle.  [[Stein's paradox]] (for example) illustrated that finding
+a "flat" or "uninformative" prior probability distribution in high dimensions is
+subtle.{{sfn|Efron|1978}}  Bayesians regard that as peripheral to the core of
+their philosophy while finding frequentism to be riddled with inconsistencies,
+paradoxes and bad mathematical behavior.  Frequentists can explain most.  Some
+of the "bad" examples are extreme situations - such as estimating the weight of
+a herd of elephants from measuring the weight of one ("Basu's elephants"), which
+allows no statistical estimate of the variability of weights.  The
+[[likelihood principle]] has been a battleground.
+===Statistical results===
+Both schools have achieved impressive results in solving real-world problems.
+Classical statistics effectively has the longer record because numerous results
+were obtained with mechanical calculators and printed tables of special
+statistical functions.  Bayesian methods have been highly successful in the
+analysis of information that is naturally sequentially sampled (radar and
+sonar).  Many Bayesian methods and some recent frequentist methods (such as the
+bootstrap) require the computational power widely available only in the last
+several decades.
+There is hint that Bayesian philosophy is "book smart" compared to Frequentist
+"street smarts".  Bayesian philosophy has sometimes been silent on shuffling the
+cards.  The "design of experiments" teaches the importance of the source of
+statistical data.  Fisher was a major contributor to the theory.
+There is active discussion about combining Bayesian and frequentist
+methods,{{sfn|Berger|2003}}{{sfn|Little|2005}} but reservations are expressed
+about the meaning of the results and reducing the diversity of approaches.
+===Philosophical results===
+Baysians are united in opposition to the limitations of frequentism, but are
+philosophically divided into numerous camps (empirical, hierarchical, objective,
+personal, subjective), each with a different emphasis.
+One (frequentist) philosopher of statistics has noted a retreat from the
+statistical field to philosophical [[probability interpretations]] over the last
+two generations.{{sfn|Mayo|2013}}  There is a perception that successes in
+Bayesian applications do not justify the supporting philosophy.{{sfn|Senn|2011}}
+Bayesian methods often create useful models that are not used for traditional
+inference and which owe little to philosophy.{{sfn|Gelman & Shalizi|2012}}
+None of the philosophical interpretations of probability (frequentist or
+Bayesian) appears robust.  The frequentist view to too rigid and limiting while
+the Bayesian view can be simultaneously objective and subjective, etc.
+===Illustrative quotations===
+* "carefully used, the frequentist approach yields broadly applicable if sometimes clumsy answers"{{sfn|Cox|2005}}
+* "To insist on unbiased [frequentist] techniques may lead to negative (but unbiased) estimates of a variance; the use of p-values in multiple tests may lead to blatant contradictions; conventional 0.95-confidence regions may actually consist of the whole real line. No wonder that mathematicians find it often difficult to believe that conventional statistical methods are a branch of mathematics."{{sfn|Bernardo|2008}}
+* "Bayesianism is a neat and fully principled philosophy, while frequentism is a grab-bag of opportunistic, individually optimal, methods."{{sfn|Efron|2013}}
+* "in multiparameter problems flat priors can yield very bad answers"{{sfn|Cox|2005}}
+* "[Bayes' rule] says there is a simple, elegant way to combine current information with prior experience in order to state how much is known. It implies that sufficiently good data will bring previously disparate observers to agreement. It makes full use of available information, and it produces decisions having the least possible error rate."{{sfn|Kass|2012?}}
+* "Bayesian statistics is about making probability statements, frequentist statistics is about evaluating probability statements."{{sfn|Gelman|2008}}
+* "[S]tatisticians are often put in a setting reminiscent of Arrow’s paradox, where we are asked to provide estimates that are informative and unbiased and confidence statements that are correct conditional on the data and also on the underlying true parameter."{{sfn|Gelman|2008}} (These are conflicting requirements.)
+* "formal inferential aspects are often a relatively small part of statistical analysis"{{sfn|Cox|2005}}
+* "The two philosophies, Bayesian and frequentist, are more orthogonal than antithetical."{{sfn|Efron|2013}}
+===Summary===
+* Bayesian theory has a mathematical advantage
+** Frequentist probability has existence and consistency problems
+** But, finding good priors to apply Bayesian theory remains (very?) difficult
+* Both theories have impressive records of successful application
+* Neither supporting philosophical interpretation of probability is robust
+* There is increasing skepticism of the connection between application and philosophy
+* Some statisticians are recommending active collaboration (beyond a cease fire)
+==The likelihood principle==
+{{main|Likelihood principle}}
+Likelihood is a synonym for probability in common usage.  In statistics it is
+reserved for probabilities that fail to meet the frequentist definition.  A
+probability refers to variable data for a fixed hypothesis while a likelihood
+refers to variable hypotheses for a fixed set of data.  Repeated measurements of
+a fixed length with a ruler generate a set of observations.  Each fixed set of
+observational conditions is associated with a probability distribution and each
+set of observations can be interpreted as a sample from that distribution – the
+frequentist view of probability.  Alternatively a set of observations may result
+from sampling any of a number of distributions (each resulting from a set of
+observational conditions).  The probabilistic relationship between a fixed
+sample and a variable distribution (resulting from a variable hypothesis) is
+termed likelihood – a Bayesian view of probability.  A set of length
+measurements may imply readings taken by careful, sober, rested, motivated
+observers in good lighting.
+A likelihood is a probability (or not) by another name which exists because of
+the limited frequentist definition of probability.  Likelihood is a concept
+introduced and advanced by [[Ronald A Fisher|Fisher]] for more than 40 years
+(although prior references to the concept exist and Fisher's support was half-hearted).{{sfn|Edwards|1999}}  The concept was accepted and substantially
+changed by [[Harold Jeffreys|Jeffreys]].{{sfn|Aldrich|2002}}  In 1962
+[[Allan Birnbaum|Birnbaum]] "proved" the likelihood principle from premises
+acceptable to most statisticians.{{sfn|Birnbaum|1962}}  The "proof" has been
+disputed by statisticians and philosophers.  The principle says that all of the
+information in a sample is contained in the [[likelihood function]], which is
+accepted as a valid probability distribution by Bayesians (but not by
+frequentists).
+Some (frequentist) significance tests are not consistent with the likelihood
+principle.  Bayesians accept the principle which is consistent with their
+philosophy (perhaps encouraged by the discomfiture of frequentists).  "[T]he
+likelihood approach is compatible with Bayesian statistical inference in the
+sense that the posterior Bayes distribution for a parameter is, by Bayes’s
+Theorem, found by multiplying the prior distribution by the likelihood
+function."{{sfn|Edwards|1999}}  Frequentists interpret the principle adversely
+to Bayesians as implying no concern about the reliability of evidence.  "The
+likelihood principle of Bayesian statistics implies that information about the
+experimental design from which evidence is collected does not enter into the
+statistical analysis of the data."{{sfn|Backe|1999}}  Many Bayesians (Savage for
+example){{sfn|Savage|1960|p=585}} recognize that implication as a vulnerability.
+The likelihood principle has become an embarrassment to both major
+philosophical schools of statistics; It has weakened both rather than favoring
+either.  Its strongest supporters claim that it offers a better foundation for
+statistics than either of the two schools.  "[L]ikelihood looks very good indeed
+when it is compared with these [Bayesian and frequentist] alternatives."{{sfn|
+Forster & Sober|2001}}  These supporters include statisticians and philosophers
+of science.{{sfn|Royall|1997}}  The concept needs further development before
+it can be regarded as a serious challenge to either existing school, but it
+seems to offer a promising compromise position.  While Bayesians acknowledge the
+importance of likelihood for calculation, they believe that the posterior
+probability distribution is the proper basis for inference.{{sfn|Lindley|2000}}
+==Modeling==
+{{main|Statistical model|Structural equation modeling}}
+Inferential statistics is based on models.  Much of classical hypothesis
+testing, for example, was based on the assumed normality of the data.  Robust
+and nonparametric statistics were developed to reduce the dependence on that
+assumption.  Bayesian statistics interprets new observations from the
+perspective of prior knowledge – assuming a modeled continuity between past and
+present.  The design of experiments assumes some knowledge of those factors to
+be controlled, varied, randomized and observed.  Statisticians are well aware of
+the difficulties in proving causation (more of a modeling limitation than a
+mathematical one), saying "[[correlation does not imply causation]]".
+More complex statistics utilizes more complex models, often with the intent of
+finding a latent structure underlying a set of variables.  As models and data
+sets have grown in complexity,<ref>Some large models attempt to predict the
+behavior of voters in the United States of America.  The population is around
+million.   Each voter may be influenced by many factors.  For some of the
+complications of voter behavior (most easily understood by the natives) see:
+http://www.stat.columbia.edu/~gelman/presentations/redbluetalkubc.pdf</ref><ref>
+Efron mentions millions of data points and thousands of parameters from
+scientific studies.</ref> foundational questions have been raised about the
+justification of the models and the validity of inferences drawn from them.  The
+range of conflicting opinion expressed about modeling is large.
+*Models can be based on scientific theory or on ad-hoc data analysis.  The approaches use different methods.  There are advocates of each.{{sfn|Tabachnick & Fidell|1996}}
+*Model complexity is a compromise.  The Akaikean information criterion and Bayesian information criterion are two less subjective approaches to achieving that compromise.{{sfn|Forster & Sober|1994}}
+*Fundamental reservations have been expressed about even simple regression models used in the social sciences.  A long list of assumptions inherent to the validity of a model is typically neither mentioned nor checked.  A favorable comparison between observations and model is often considered sufficient.{{sfn|Freedman|1995}}
+*Bayesian statistics focuses so tightly on the posterior probability that it ignores the fundamental comparison of observations and model.{{sfn|Gelman & Shalizi|2012}}
+*Traditional observation-based models are inadequate to solve many important problems.  A much wider range of models, including algorithmic models, must be utilized.  "If the model is a poor emulation of nature, the conclusions may be wrong."{{sfn|Breiman|2001}}
+*Modeling is often poorly done (the wrong methods are used) and poorly reported.{{sfn|Chin|?}}
+In the absence of a strong philosophical consensus review of statistical
+modeling, many statisticians accept the cautionary words of statistician
+[[George E. P. Box|George Box]], "[A]ll models are wrong, but some are useful."
+(wikiquote)
+==Other reading==
+For a short introduction to the foundations of statistics, see ch.&nbsp;8 ("Probability and statistical inference") of ''Kendall's Advanced Theory of Statistics'' (6th edition, 1994).
+In his book ''Statistics As Principled Argument'', [[Robert P. Abelson]] articulates the position that statistics serves as a standardized means of settling disputes between scientists who could otherwise each argue the merits of their own positions ''[[ad infinitum]]''. From this point of view, statistics is a form of rhetoric; as with any means of settling disputes, statistical methods can succeed only as long as all parties agree on the approach used.
+==See also==
+{{Portal|Statistics}}
+{{colbegin}}
+*[[Philosophy of statistics]]
+*[[History of statistics]]
+*[[Philosophy of probability]]
+*[[Philosophy of mathematics]]
+*[[Philosophy of science]]
+*[[Evidence]]
+*[[Probability interpretations]]
+*[[Founders of statistics]]
+{{colend}}
+==Notes==
+{{reflist|colwidth=25em}}
+==References==
+*{{Cite book |last=Abelson |first=Robert P. |authorlink=Robert P. Abelson |title=Statistics as Principled Argument |year=1995 |publisher=Lawrence Erlbaum Associates |isbn=0-8058-0528-1 |quote=... the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. }}
+*Stuart A., Ord J.K. (1994). ''Kendall's Advanced Theory of Statistics, volume I: Distribution Theory'' (Edward Arnold).
+* {{cite journal|last=Aldrich|first=John|title=How likelihood and identification went Bayesian|journal=International Statistical Review|volume=70|issue=1|pages=79–98|year=2002|ref=harv}}
+* {{cite journal|last=Backe|first=Andrew|title=The likelihood principle and the reliability of experiments|journal=Philosophy of Science|pages=S354-S361|year=1999|ref=harv}}
+* {{cite journal|last=Berger|first=James O.|title=Could Fisher, Jeffreys and Neyman Have Agreed on Testing?|journal=Statistical Science|year=2003|volume=18|issue=1|pages=1–32|ref=harv}}
+* {{cite journal|last=Bernardo|first=Jose M.|title=Comment on Article by Gelman|journal=Bayesian Analysis|year=2008|volume=3|issue=3|page=453|doi=10.1214/08-BA318REJ|ref=harv}}
+* {{cite journal|last=Birnbaum|first= A.|title=On the foundations of statistical inference|journal=J. Amer. Statist. Ass|volume=57|pages=269–326|year=1962|ref=harv}}
+* {{cite book | editor1-last = Bandyopadhyay | editor1-first = Prasanta | others = Malcolm Forster | title = Philosophy of statistics |series= Handbook of the Philosophy of Science|volume= 7 | publisher = North-Holland | location = Oxford | year = 2011 | isbn = 978-0444518620 }}  The text is a collection of essays.
+* {{cite journal|last=Breiman|first=Leo |title=Statistical Modeling: The Two Cultures|journal=Statistical Science|volume=16|issue=3|pages=199–231|year=2001|ref=harv}}
+* {{cite web | last = Chin | first = Wynne W.| title = Structural Equation Modeling in IS Research - Understanding the LISREL and PLS perspective | url = http://disc-nt.cba.uh.edu/chin/ais/|year=?|ref=harv}}  University of Houston lecture notes?
+* {{cite web | last = Cox | first = D. R. | title = Frequentist and Bayesian Statistics: a Critique | url = http://www.physics.ox.ac.uk/phystat05/proceedings/default.htm |year=2005|ref=harv}} Proceedings of the Statistical Problems in Particle Physics, Astrophysics and Cosmology
+* {{cite book |last1= de Finetti |first1= Bruno |authorlink1= Bruno de Finetti |editor1-first= H. E. |editor1-last= Kyburg  |others= H. E. Smokler |title= Studies in Subjective Probability |year= 1964 |publisher= Wiley |location= New York |pages= 93–158 |chapter= Foresight: its Logical laws, its Subjective Sources|ref=harv}} Translation of the 1937 French original with later notes added.
+* {{cite web | last = Edwards | first = A.W.F. | title = Likelihood | url = http://www.cimat.mx/reportes/enlinea/D-99-10.html |year=1999|ref=harv}}  Preliminary version of an article for the International Encyclopedia of the Social and Behavioral Sciences.
+* {{cite journal|last= Efron|first=Bradley|title=A 250-Year Argument: Belief, Behavior, and the Bootstrap|journal=Bulletin (new series) of the
+American Mathematical Society|year=2013|volume=50|issue=1|pages= 129–146|doi=|ref=harv}}
+* {{cite journal|last=Efron|first=Bradley|title=Controversies in the foundations of statistics|journal=The American Mathematical Monthly|year=1978|volume=85|issue=4|pages=231–246 |doi=10.2307/2321163| url = http://mathdl.maa.org/images/upload_library/22/Ford/BradleyEfron.pdf |ref=harv}}
+* {{cite journal|last=Fienberg|first=Stephen E.|title=|journal=Bayesian Analysis|year=2006|volume=1|issue=1|pages=1–40|ref=harv}}
+* {{cite book | last = Fisher | first =  R. A. | title = Statistical Methods for Research Workers | publisher =  Oliver and Boyd | location = Edinburgh | year =  1925 |ref=harv}}
+* {{cite book | last = Fisher | first = Sir Ronald A. | title = Design of Experiments | publisher =  Oliver and Boyd | location = Edinburgh | year =  1935 |ref=harv}}
+* {{cite journal|last=Fisher|first=R|title=Statistical Methods and Scientific Induction|journal=Journal of the Royal Statistical Society, Series B|year=1955 |volume=17|issue=1|pages=69–78|url=http://www.phil.vt.edu/dmayo/PhilStatistics/Triad/Fisher%201955.pdf|ref=harv}}
+* {{cite book | last = Fisher | first = Sir Ronald A. | title = The logic of scientific inference | publisher =  Oliver and Boyd | location = Edinburgh | year =  1956 |ref=harv}}
+* {{cite journal|last1=Forster|first1=Malcolm|last2=Sober|first2=Elliott|title=How to Tell when Simpler, More Unified, or Less Ad Hoc Theories will Provide More Accurate Predictions|journal=British Journal for the Philosophy of Science|issue=45|pages=1–36|year=1994|ref=harv}}
+* {{cite journal|last1=Forster|first1=Malcolm|last2=Sober|first2=Elliott|title=Why likelihood|journal=Likelihood and evidence|pages=89–99|year=2001|ref=harv}}
+* {{cite journal|last=Freedman|first=David|title=Some issues in the foundation of statistics|journal=Foundations of Science|pages=19–39|volume=1|year=1995/6|ref=harv}}
+* {{cite journal|last1=Gelman|first1=Andrew|title=Rejoiner|journal=Bayesian Analysis|year=2008|volume=3|issue=3|pages=467–478|doi=10.1214/08-BA318REJ|ref=harv}} A joke escalated into a serious discussion of Bayesian problems by 5 authors (Gelman, Bernardo, Kadane, Senn, Wasserman) on pages 445-478.
+* {{cite journal|last1=Gelman|first1=Andrew|last2=Shalizi|first2=Cosma Rohilla|title=Philosophy and the practice of Bayesian statistics|journal=British Journal of Mathematical and Statistical Psychology|year=2012|doi=10.1111/j.2044-8317.2011.02037.x|ref=harv}}
+* {{cite book|title=The Empire of Chance: How Probability Changed Science and Everyday Life|last=Gigerenzer|first=Gerd|coauthors=Zeno Swijtink, Theodore Porter, Lorraine Daston, John Beatty, Lorenz Kruger|year=1989|publisher=Cambridge University Press|chapter=Part 3: The Inference Experts|isbn=978-0-521-39838-1|pages=70–122|ref=harv}}
+* {{cite journal|last=Halpin|first=P F|title=Inductive Inference or Inductive Behavior: Fisher and Neyman: Pearson Approaches to Statistical Testing in Psychological Research (1940–1960)|journal=The American Journal of Psychology|date=Winter 2006 |volume=119|issue=4|pages=625–653|jstor=20445367|doi=10.2307/20445367|pmid=17286092|last2=Stam|first2=HJ|ref=harv}}
+* {{cite web | last1 = Hubbard | first1 = Raymond | last2 = Bayarri | first2 = M. J. | title = P Values are not Error Probabilities
+ | url = http://ftp.isds.duke.edu/WorkingPapers/03-26.pdf |year=2003?|ref=harv}}  A working paper that explains the difference between Fisher's evidential p-value and the Neyman–Pearson Type I error rate <math>\alpha</math>.
+* {{cite book | last = Jeffreys | first = H. | title =  The theory of probability | publisher = Oxford University Press | year = 1939 |ref=harv}}
+* {{cite web | last = Kass | first = | title = Why is it that Bayes’ rule has not only captured the attention of so many people but inspired a religious devotion and contentiousness, repeatedly across many years? | url = http://www.stat.cmu.edu/~kass/papers/about-bayes-rule.pdf |year=2012?|ref=harv}}
+* {{cite journal|last=Lehmann|first=E. L.|title=The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory or Two?|journal=Journal of the American Statistical Association|volume=88|issue=424|pages=1242–1249|date=December 1993|ref=harv}}
+* {{cite book | last = Lehmann | first = E. L. | title = Fisher, Neyman, and the creation of classical statistics | publisher = Springer | location = New York | year = 2011 | isbn = 978-1441994998 |ref=harv}}
+* {{cite book|title=Testing Statistical Hypotheses|edition=3E|isbn=0-387-98864-5|last1=Lehmann|first1=E.L.|first2=Joseph P.|last2=Romano|year=2005|publisher=Springer|location=New York|ref=harv}}
+* {{cite journal|last=Lenhard|first=Johannes|title=Models and Statistical Inference: The Controversy between Fisher and Neyman–Pearson|journal=Brit. J. Phil. Sci.|volume=57|pages=69–91|year=2006|ref=harv}}
+* {{cite journal | last = Little | first = Roderick J. | title = Calibrated Bayes: A Bayes/Frequentist Roadmap |volume=60 |issue=3|year= 2006|ref=harv}}
+*{{Cite book |last=Lindley |first=D.V.| author-link=Dennis Lindley |year=2000| title=The philosophy of statistics| journal=[[Journal of the Royal Statistical Society, Series D]]| volume=49| pages=293–337|doi=10.1111/1467-9884.00238|issue=3}}
+* {{cite web | last = Louçã | first = Francisco | title = Should The Widest Cleft in Statistics-How and Why Fisher opposed Neyman and Pearson
+ | url = http://www.repository.utl.pt/bitstream/10400.5/2327/1/wp022008.pdf |year=2008|ref=harv}}  Working paper contains numerous quotations from the original sources of the dispute.
+* {{cite journal|last=Mayo|first=Deborah G.|title=Discussion: Bayesian Methods: Applied? Yes. Philosophical Defense? In Flux|journal=The American Statistician|date=February 2013|volume=67|issue=1|pages=11–15|doi=10.1080/00031305.2012.752410|ref=harv}}
+* {{cite journal|last=Neyman|first=J|title=On the Problem of the most Efficient Tests of Statistical Hypotheses|journal=Phil. Trans. R. Soc. Lond. A|date=January 1, 1933|volume=231|issue=694–706|pages=289–337|doi=10.1098/rsta.1933.0009|last2=Pearson|first2=E. S.|ref=harv}}
+* {{cite book |last=Neyman|first=J|title=Joint statistical papers of J.Neyman and E.S.Pearson|year=1967|publisher=Cambridge University Press|ref=harv}}
+* {{cite journal|last=Neyman|first=Jerzy|title=Note on an Article by Sir Ronald Fisher|journal=[[Journal of the Royal Statistical Society, Series B]]|year=1956|volume=18|issue=2|pages=288–294|ref=harv}}
+* {{cite book | last = Royall | first = Richard | title = Statistical evidence : a likelihood paradigm | publisher = Chapman & Hall | location = London New York | year = 1997 | isbn = 978-0412044113 }}
+* {{Cite book |last = Savage  |first = L.J.  |authorlink = Leonard Jimmie Savage |year = 1972  |title = Foundations of Statistics (second edition) |ref=harv}}
+* {{cite journal|last=Senn|first=Stephen|title=You May Believe You Are a Bayesian But You Are Probably Wrong|journal=RMM|year=2011|volume=2|pages=48–66|ref=harv}}
+* {{cite journal|last1=Sotos|first1=Ana Elisa Castro|last2=Vanhoof|first2=Stijn|last3=Noortgate|first3=Wim Van den|last4=Onghena|first4=Patrick|title=Students' Misconceptions of Statistical Inference: A Review of the Empirical Evidence from Research on Statistics Education|journal=Educational Research Review|volume=2|pages=98–113|year=2007|ref=harv}}
+* {{cite book |last1=Tabachnick|first1=Barbara G. |last2=Fidell|first2=Linda S. |title=Using Multivariate Statistics |edition=3rd |year=1996 |isbn=0-673-99414-7}} "Principal components is an empirical approach while factor analysis and structural equation modeling tend to be theoretical approaches."  p 27
+* {{cite web |last=Yu |first=Yue |title=Bayesian vs. Frequentist |url=http://imyy.net/research/BSTT566__Slides.pdf |format=pdf |year=2009 |ref=harv}} Lecture notes? University of Illinois at Chicago
+==Further reading==
+*{{Cite book |last=Barnett | first=Vic | year=1999 | title=Comparative Statistical Inference | edition= 3rd| publisher=Wiley | isbn=978-0-471-97643-1}}
+*{{Cite book |last=Cox | first = David R. | author-link=David Cox (statistician)| title=Principles of Statistical Inference | publisher=[[Cambridge University Press]] | year=2006|isbn=978-0-521-68567-2 }}
+*{{Cite book |last= Efron | first=Bradley | author-link=Bradley Efron | title=Why Isn't Everyone a Bayesian? (with discussion)| journal= [[The American Statistician]] | volume= 40 | issue= 1 | year=1986 | pages= 1–11 | doi= 10.2307/2683105 |  jstor=2683105}}
+*{{Cite book |last=Good | first=I. J. | author-link=I. J. Good | title=The Interface Between Statistics and Philosophy of Science | journal=Statistical Science | volume= 3| issue=4 | year=1988 |pages=386–397 | doi=10.1214/ss/1177012754 | jstor=2245388}}
+*[[Joseph Born Kadane|Kadane J.B.]], Schervish M.J., Seidenfeld T. (1999), ''Rethinking the Foundations of Statistics'' ([[Cambridge University Press]]).  [Bayesian.]
+*{{Cite book |last=Mayo |first=Deborah G.| title=Did Pearson reject the Neyman-Pearson philosophy of statistics? | journal=Synthese |volume=90 |pages=233–262 |year= 1992 | doi=10.1007/BF00485352| issue=2}}
+==External links==
+*[http://scholar.google.co.uk/scholar?cites=9531312933296806388 Citations of Savage (1972)] at [[Google Scholar]]. [Over 10000 citations.]
+*Stanford Encyclopedia of Philosophy [http://plato.stanford.edu/entries/probability-interpret/ entry] on probability interpretations.
+[[Category:Philosophy of science]]
+[[Category:Statistical inference]]
+[[Category:Statistics]]

Dividend payout ratio: Difference between revisions

Revision as of 11:18, 9 November 2013

Fisher's "significance testing" vs Neyman-Pearson "hypothesis testing"

Significance testing

Hypothesis testing

Grounds of disagreement

Related history

Contemporary opinion

Summary

Bayesian inference versus frequentist inference

Major contributors

Contrasting approaches

Frequentist inference

Bayesian inference

Comparisons of characteristics

Mathematical results

Statistical results

Philosophical results

Illustrative quotations

Summary

The likelihood principle

Modeling

Other reading

See also

Notes

References

Further reading

External links

Navigation menu

Search