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Dataplot Vol 1 Vol 2

ANDERSON DARLING K SAMPLE TEST

Name:
    ANDERSON DARLING K SAMPLE TEST
Type:
    Analysis Command
Purpose:
    The k-sample Anderson-Darling test is a nonparametric statistical procedure that tests the hypothesis that the populations from which two or more groups of data were drawn are identical. Each group should be an independent random sample from a population.
Description:
    This test is part of the MIL-HDBK-17 standard. In the terminology of MIL-HDBK-17, data can be either "structured" (i. e., groups) or "unstructured" (i.e., ungrouped). Unstructured data can often be simpler to analyze. Therefore the Anderson-Darling k-sample test is used to determine if a structured data set can in fact be treated as an unstructured data set. Dataplot supports most of the techniques in chapter 8 of the MIL-HDBK-17 as support for the RECIPE analysis.

    The k-sample Anderson-Darling statistic is

      \( ADK = \frac{n-1}{n^2(k-1)} \sum_{i=1}^{k}{[\frac{1}{n_i} \sum_{j=1}^{L}{h_j \frac{(nF_{ij} - n_{i}H_{j})^2}{H_j(n-H_j) - nh_{j}/4}}]} \)

    where

    • hj = the number of values in the combined samples equal to zj
    • Hj = the number of values in the combined samples less than zj plus one half the number of values in the combined samples equal to zj
    • Fij = the number of values in the i-th group which are less than zj plus one half the number of values in this group which are equal to zj

    where k is the number of samples (groups), ni is the number of observations in group i, xij is the j-th observation in the i-th group, and z1, z2 ..., zL are the distinct values in the combined data set ordered from smallest to largest (L is less than n if there are tied observations).

    Chapter 8 of the MIL-HDBK-17 derives the formulas for the critical values of the Anderson-Darling test statistic. These formulas are rather involved and not given here.

    Dataplot uses the ANDYK routine from the MIL-HDBK-17 to compute the Anderson-Darling k sample test.

Syntax:
    ANDERSON DARLING K SAMPLE TEST <y> <groupid> <SUBSET/EXCEPT/FOR qualification>
    where <y> is the response variable;
              <groupid> is group (sample) identifier variable;
    and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
    ANDERSON DARLING K SAMPLE TEST Y1 GROUP
    ANDERSON DARLING K SAMPLE TEST Y1 GROUP SUBSET GROUP > 2
Note:
    The following statistics are also supported:

      LET A = ANDERSON DARLING K SAMPLE TEST Y X

      LET ALPHA = <value>
      LET A = ANDERSON DARLING K SAMPLE TEST CRITICAL VALUE Y X

    with Y denoting the response variable, X denoting the group-id variable, and ALPHA denoting the significance level for the critical value.

    In addition to the above LET command, built-in statistics are supported for about 20+ different commands (enter HELP STATISTICS for details).

Default:
    None
Synonyms:
    ANDERSON DARLING K SAMPLE is a synonym for ANDERSON DARLING K SAMPLE TEST.
Related Commands:
    LEVENE TEST = Compute Levene's test for homogeneity of variances.
    BOX PLOT = Generate a box plot.
    RECIPE FIT = Perform a RECIPE analysis.
    GRUBBS TEST = Compute a Grubbs test for outliers.
    GOODNESS OF FIT = Assess univariate distributional goodness-of-fit using Anderson-Darling, Kolmogorov-Smirnov, chi-square, or PPCC method.
Reference:
    "MIL-HDBK-17 Volume 1: Guidelines for Characterization of Structural Materials", Depeartment of Defense, chapter 8. The URL for MIL-HDBK-17 is http://mil-17.udel.edu/.
Applications:
    Tolerance Studies in Reliability of Materials
Implementation Date:
    1998/6
Program:
     
    SKIP 25
    READ VANGEL32.DAT Y X B
    SET WRITE DECIMALS 4
    ANDERSON DARLING K SAMPLE TEST Y X
        
        The following output is generated:
        
        
                Anderson-Darling K-Sample Test for Common Groups
     
    Response Variable: Y
    Group-ID Variable: X
     
    H0: The Groups Are Homogeneous
    Ha: The Groups Are Not Homogeneous
     
    Summary Statistics:
    Total Number of Observations:                        45
    Number of Groups:                                     3
    Minimum Batch Size:                                  15
    Maximum Batch Size:                                  15
     
    Test Statistic Value:                          155.3624
    Test Statistic Standard Error:                   0.5108
     
     
                Conclusions (Upper 1-Tailed Test)
     
    ------------------------------------------------------------------------
                                                                        Null
            Null   Significance           Test       Critical     Hypothesis
      Hypothesis          Level      Statistic    Region (>=)     Conclusion
    ------------------------------------------------------------------------
     Homogeneous          50.0%       155.3624         1.1524         REJECT
     Homogeneous          75.0%       155.3624         1.4969         REJECT
     Homogeneous          90.0%       155.3624         1.8070         REJECT
     Homogeneous          95.0%       155.3624         1.9926         REJECT
     Homogeneous          97.5%       155.3624         2.1536         REJECT
     Homogeneous          99.0%       155.3624         2.3407         REJECT
     Homogeneous          99.9%       155.3624         2.7310         REJECT
        
Date created: 06/05/2001
Last updated: 12/04/2023

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