Statistics[ChiSquareIndependenceTest] - apply the chisquare test for independence in a matrix
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Calling Sequence
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ChiSquareIndependenceTest(X, options)
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Parameters
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X
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Matrix of categorized data
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options
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(optional) equation(s) of the form option=value where option is one of level or output; specify options for the ChiSquareIndependenceTest function
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Description
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The ChiSquareIndependenceTest function computes the chisquare test for independence in a matrix. This test attempts to determine if two factors can be considered to be independent of one another for purposes of analysis.
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The first parameter X is a matrix of categorized data samples.
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Options
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The options argument can contain one or more of the options shown below.
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This option is used to specify the level of the analysis (minimum criteria for a data set to be considered independent). By default this value is 0.05.
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output='report', 'statistic', 'pvalue', 'criticalvalue', 'distribution', 'hypothesis', or list('statistic', 'pvalue', 'criticalvalue', 'distribution', 'hypothesis')
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This option is used to specify the desired format of the output from the function. If 'report' is specified then a module containing all output from this test is returned. If a single parameter name is specified other than 'report' then that quantity alone is returned. If a list of parameter names is specified then a list containing those quantities in the specified order will be returned.
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Notes
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This test generates a complete report of all calculations in the form of a userinfo message. In order to access this report, specify infolevel[Statistics] := 1.
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Examples
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Specify the matrices of categorized data values.
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Perform the independence test on the first sample.
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Chi-Square Test for Independence
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Null Hypothesis:
Two attributes within a population are independent of one another
Alt. Hypothesis:
Two attributes within a population are not independent of one another
Dimensions: 3
Total Elements: 95
Distribution: ChiSquare(2)
Computed statistic: 10.7122
Computed pvalue: 0.00471928
Critical value: criticalvalue
Result: [Rejected]
There exists statistical evidence against the null hypothesis
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Perform the independence test on the second sample.
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Chi-Square Test for Independence
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Null Hypothesis:
Two attributes within a population are independent of one another
Alt. Hypothesis:
Two attributes within a population are not independent of one another
Dimensions: 3
Total Elements: 38
Distribution: ChiSquare(2)
Computed statistic: 0.128915
Computed pvalue: 0.937576
Critical value: criticalvalue
Result: [Accepted]
There is no statistical evidence against the null hypothesis
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References
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Kanju, Gopal K. 100 Statistical Tests. London: SAGE Publications Ltd., 1994.
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Sheskin, David J. Handbook of Parametric and Nonparametric Statistical Procedures. London: CRC Press, 1997.
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Download Help Document
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