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Dataplot Vol 1 Auxiliary Chapter

WILKS SHAPIRO NORMALITY TEST

Name:
    WILKS SHAPIRO NORMALITY TEST
Type:
    Analysis Command
Purpose:
    Perform a Wilks Shapiro test for normality.
Description:
    The Wilks Shapiro test statistic is defined as:

      W = {SUM(w(i)X'(i)}**2/[SUM(X(i)-XBAR)**2]

    where the summation is from 1 to n and n is the number of observations. The array X contains the original data, X' are the ordered data, XBAR is the sample mean of the data, and w'=(w1, w2, ... , wn) or

      w'=M'V**(-1)[(N'V**(-1))(V**(-1)M)]**(-1/2)

    M denotes the expected values of standard normal order statistics for a sample of size n and V is the corresponding covariance matrix.

    W may be thought of as the squared correlation coefficient between the ordered sample values (X') and the wi. The wi are approximately proportional to the normal scores Mi. W is a measure of the straightness of the normal probability plot, and small values indicate departures from normality. Note that the Dataplot PPCC PLOT command is based on a similar concept.

    Monte Carlo simulations studies have indicated that the Wilks-Shapiro test has good power properties for a wide range of alternative distributions.

Syntax:
    WILKS SHAPIRO NORMALITY TEST <y> <SUBSET/EXCEPT/FOR qualification>
    where <y> is the response variable being tested;
    and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
    WILKS SHAPIRO NORMALITY TEST Y1
    WILKS SHAPIRO NORMALITY TEST Y1 SUBSET TAG > 2
Note:
    Dataplot uses Algorithm AS R94 (SWILK sub routine) from the Applied Statistics Journal, 1995, Vol. 44, No. 4. This routine should produce accurate critical values for N <= 5,000.
Default:
    None
Synonyms:
    The following are synonyms for the WILKS SHAPIRO NORMALITY TEST.

      WILKS SHAPIRO TEST Y WILKS SHAPIRO Y
Related Commands:
    ANDERSON DARLING TEST = Compute the Anderson-Darling test for normality.
    CHI-SQUARE GOODNES OF FIT = Compute the Chi-Square goodness of fit test.
    KOLMOGOROV-SMIRNOV GOODNES OF FIT = Compute the Kolmogorov-Smirnov goodness of fit test.
    PROBABILITY PLOT = Generates a probability plot.
    PPCC PLOT = Generates a ppcc plot.
Reference:
    Shapiro, S. S. and Wilk, M. B. (1965). Biometrika, 52, 591-611.
Applications:
    Distributional Fitting, Assumption Testing
Implementation Date:
    2000/1
Program:
    SKIP 25
    READ ZARR13.DAT Y
    WILKS SHAPIRO NORMALITY TEST Y

    The following outpout is generated:

                   WILKS SHAPIRO TEST FOR NORMALITY
      
     1. STATISTICS:
           NUMBER OF OBSERVATIONS                =      195
           LOCATION PARAMETER                    =    9.261460
           SCALE PARAMETER                       =   0.2278881E-01
      
           WILKS SHAPIRO TEST STATISTIC VALUE =   0.9982718
      
     2. CRITICAL VALUES:
           P-VALUE      =   0.9992256
      
     3. CONCLUSIONS:
           AT THE 90% LEVEL, WE ACCEPT THE NORMALITY ASSUMPTION.
           AT THE 95% LEVEL, WE ACCEPT THE NORMALITY ASSUMPTION.
           AT THE 97.5% LEVEL, WE ACCEPT THE NORMALITY ASSUMPTION.
           AT THE 99% LEVEL, WE ACCEPT THE NORMALITY ASSUMPTION.
      
        

Date created: 6/5/2001
Last updated: 4/4/2003
Please email comments on this WWW page to alan.heckert@nist.gov.