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Statistics[ChiSquareIndependenceTest] - apply the chisquare test for independence in a matrix
Calling Sequence
ChiSquareIndependenceTest(X, options)
Parameters
X
-
Matrix of categorized data
options
(optional) equation(s) of the form option=value where option is one of level or output; specify options for the ChiSquareIndependenceTest function
Description
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.
The first parameter X is a matrix of categorized data samples.
Options
The options argument can contain one or more of the options shown below.
level=float
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.
output='report', 'statistic', 'pvalue', 'criticalvalue', 'distribution', 'hypothesis', or list('statistic', 'pvalue', 'criticalvalue', 'distribution', 'hypothesis')
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.
Notes
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.
Examples
Specify the matrices of categorized data values.
Perform the independence test on the first sample.
Chi-Square Test for Independence -------------------------------- 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
Perform the independence test on the second sample.
Chi-Square Test for Independence -------------------------------- 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
See Also
Statistics, Statistics[Computation]
References
Kanju, Gopal K. 100 Statistical Tests. London: SAGE Publications Ltd., 1994.
Sheskin, David J. Handbook of Parametric and Nonparametric Statistical Procedures. London: CRC Press, 1997.
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