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From "Phil Steitz (JIRA)" <j...@apache.org>
Subject [jira] Resolved: (MATH-160) Chi-Square Test for Comparing two binned Data Sets
Date Sun, 24 Jun 2007 21:15:26 GMT

     [ https://issues.apache.org/jira/browse/MATH-160?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Phil Steitz resolved MATH-160.
------------------------------

    Resolution: Fixed

Applied a modified version of the patch, along with test cases, verified against DATAPLOT
Modifications:
* Changed input array data type to long[].  This is consistent with other ChiSquare tests
and with the specification of the test (i.e., it is not clear what floats as arguments would
mean)
* Added weighting as specified in the NIST reference provided to adjust for possibly different
bin sums for the two samples. 



> Chi-Square Test for Comparing two binned Data Sets
> --------------------------------------------------
>
>                 Key: MATH-160
>                 URL: https://issues.apache.org/jira/browse/MATH-160
>             Project: Commons Math
>          Issue Type: New Feature
>            Reporter: Matthias Hummel
>            Priority: Minor
>             Fix For: 1.2
>
>         Attachments: commons-math.patch
>
>
> Current Chi-Square test implementation only supports standard Chi-Square testing with
respect to known distribution. We needed testing for comparison of two sample data sets where
the distribution can be unknown. For this case the Chi-Square test has to be computed in a
different way so that both error contributions (one for each sample data set) are taken into
account. See Press et. al, Numerical Recipes, Second Edition, formula 14.3.2.

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