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In [[statistics]], the '''Shapiro–Wilk test''' tests the [[null hypothesis]] that a [[statistical sample|sample]] ''x''<sub>1</sub>, ..., ''x''<sub>''n''</sub> came from a [[normal distribution|normally distributed]] population. It was published in 1965 by Samuel Shapiro and [[Martin Wilk]].<ref>{{cite journal
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|last=Shapiro |first=S. S.
|last2=Wilk |first2=M. B. |authorlink2=Martin Wilk
|year=1965
|title=An analysis of variance test for normality (complete samples)
|journal=[[Biometrika]]
|volume=52 |issue=3-4 |pages=591–611
|doi=10.1093/biomet/52.3-4.591 |jstor=2333709 | mr = 205384
}}</ref>
 
The [[test statistic]] is:
 
:<math>W = {\left(\sum_{i=1}^n a_i x_{(i)}\right)^2 \over \sum_{i=1}^n (x_i-\overline{x})^2}</math>
 
where
 
* <math>x_{(i)}</math> (with parentheses enclosing the subscript index ''i'') is the ''i''th [[order statistic]], i.e., the ''i''th-smallest number in the sample;
* <math>\overline{x} = \left( x_1 + \cdots + x_n \right) / n</math> is the sample mean;
* the constants <math>a_i</math> are given by<ref>{{cite journal
|last=Shapiro |first=S. S.
|last2=Wilk |first2=M. B. |authorlink2=Martin Wilk
|year=1965
|title=An analysis of variance test for normality (complete samples)
|journal=[[Biometrika]]
|volume=52 |issue=3-4 |pages=591–611
|doi=10.1093/biomet/52.3-4.591 |jstor=2333709 | mr = 205384
}} p.&nbsp;593</ref>
 
::<math>(a_1,\dots,a_n) = {m^\top V^{-1} \over (m^\top V^{-1}V^{-1}m)^{1/2}}</math>
 
:where
 
::<math>m = (m_1,\dots,m_n)^\top\,</math>
 
:and <math>m_1,\ldots,m_n</math> are the [[expected value]]s of the [[order statistic]]s of [[independent and identically distributed random variables]] sampled from the standard normal distribution, and <math>V</math> is the [[covariance matrix]] of those order statistics.
 
The user may reject the null hypothesis if <math>W</math> is too small.<ref>{{cite journal
|last=Shapiro |first=S. S.
|last2=Wilk |first2=M. B. |authorlink2=Martin Wilk
|year=1965
|title=An analysis of variance test for normality (complete samples)
|journal=[[Biometrika]]
|volume=52 |issue=3-4 |pages=591–611
|doi=10.1093/biomet/52.3-4.591 |jstor=2333709 | mr = 205384
}} p.&nbsp;605</ref>
 
It can be interpreted via a [[Q-Q plot]].
 
==Interpretation==
Recalling that the null hypothesis is that the population is normally distributed, if the [[p-value]] is less than the chosen [[alpha level]], then the null hypothesis is rejected (i.e. one concludes the data are not from a normally distributed population).  If the p-value is greater than the chosen alpha level, then one does not reject the null hypothesis that the data came from a normally distributed population.  E.g. for an alpha level of 0.05, a data set with a p-value of 0.32 does not result in rejection of the hypothesis that the data are from a normally distributed population.<ref>{{cite web |url= http://www.jmp.com/support/faq/jmp2085.shtml |title=How do I interpret the Shapiro-Wilk test for normality?
|first= |last= |work=JMP |year=2004 |accessdate=March 24, 2012}}</ref>
 
==See also==
* [[Anderson–Darling test]]
* [[Cramér–von Mises criterion]]
* [[Kolmogorov–Smirnov test]]
* [[Normal probability plot]]
* [[Ryan–Joiner test]]
* [[Watson test]]
 
{{primary sources|date=May 2012}}
 
==References==
{{Ibid|date=May 2012}}
<references/>
 
==External links==
* [http://www.answers.com/topic/samuel-sanford-shapiro Samuel Sanford Shapiro]
* [http://lib.stat.cmu.edu/apstat/R94 Algorithm AS R94 (Shapiro Wilk) FORTRAN code]
* [http://cran.us.r-project.org/doc/manuals/R-intro.html#Examining-the-distribution-of-a-set-of-data Shapiro–Wilk Normality Test in R]
 
{{Statistics}}
 
{{DEFAULTSORT:Shapiro-Wilk Test}}
[[Category:Normality tests]]

Latest revision as of 12:02, 8 November 2014

Greetings. Let me begin by telling you the author's title - Phebe. My family members lives in Minnesota and my family loves it. I used to be unemployed but now I am a librarian and the wage has been really fulfilling. To gather coins is what her family and her appreciate.

Feel free to surf to my website; www.webmdbook.com