81 lines
2.0 KiB
Plaintext
81 lines
2.0 KiB
Plaintext
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{{alias}}( x[, options] )
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Performs a chi-square independence test.
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For a two-way contingency table `x` (represented as a two-dimensional
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`ndarray` or `array` of `arrays`), the null hypothesis that the joint
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distribution of the cell counts is the product of the row and column
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marginals is tested, i.e. whether the row and column variables are
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independent.
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The function returns an object containing the test statistic, p-value, and
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decision.
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Parameters
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----------
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x: (MatrixLike|Array<Array>)
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Two-way table of cell counts.
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options: Object (optional)
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Options.
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options.alpha: number (optional)
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Significance level of the hypothesis test. Must be on the interval
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[0,1]. Default: 0.05.
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options.correct: boolean (optional)
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Boolean indicating whether to use Yates' continuity correction when
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provided a 2x2 contingency table. Default: true.
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Returns
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-------
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out: Object
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Test result object.
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out.alpha: number
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Significance level.
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out.rejected: boolean
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Test decision.
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out.pValue: number
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Test p-value.
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out.statistic: number
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Test statistic.
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out.df: number
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Degrees of freedom.
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out.expected: ndarray
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Expected cell counts.
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out.method: string
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Test name.
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out.print: Function
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Function to print formatted output.
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Examples
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--------
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// Provide expected probabilities...
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> var x = [ [ 20, 30 ], [ 30, 20 ] ];
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> var out = {{alias}}( x )
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{ 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }
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> out.print()
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// Set significance level...
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> var opts = { 'alpha': 0.1 };
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> out = {{alias}}( x, opts )
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{ 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }
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> out.print()
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// Disable Yates' continuity correction (primarily used with small counts):
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> opts = { 'correct': false };
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> out = {{alias}}( x, opts )
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{...}
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See Also
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--------
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