repl.txt

{{alias}}( x[, options] )
    Performs a chi-square independence test.

    For a two-way contingency table, the function computes a chi-square
    independence test for the null hypothesis that the joint distribution of the
    cell counts is the product of the row and column marginals (i.e. that the
    row and column variables are independent).

    The chi-square approximation may be incorrect if the observed or expected
    frequencies in each category are too small. Common practice is to require
    frequencies greater than five. The Yates' continuity correction is enabled
    by default for 2x2 tables to account for this, although it tends to
    over-correct.

    The function returns an object containing the test statistic, p-value, and
    decision.

    Parameters
    ----------
    x: ndarray|Array<Collection<number>>
        Two-way table of observed frequencies.

    options: Object (optional)
        Options.

    options.alpha: number (optional)
        Significance level of the hypothesis test. Must be on the interval
        [0,1]. Default: 0.05.

    options.correct: boolean (optional)
        Boolean indicating whether to use Yates' continuity correction when
        provided a 2x2 contingency table. Default: true.

    Returns
    -------
    out: Object
        Test results object.

    out.alpha: number
        Significance level.

    out.rejected: boolean
        Test decision.

    out.pValue: number
        Test p-value.

    out.statistic: number
        Test statistic.

    out.df: number
        Degrees of freedom.

    out.expected: ndarray
        Expected frequencies.

    out.method: string
        Test name.

    out.toString: Function
        Serializes results as formatted output.

    out.toJSON: Function
        Serializes results as JSON.

    Examples
    --------
    > var x = [ [ 20, 30 ], [ 30, 20 ] ];
    > var out = {{alias}}( x );
    > var o = out.toJSON()
    { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }
    > out.toString()

    // Set significance level...
    > var opts = { 'alpha': 0.1 };
    > out = {{alias}}( x, opts );
    > o = out.toJSON()
    { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }
    > out.toString()

    // Disable Yates' continuity correction (primarily used with small counts):
    > opts = { 'correct': false };
    > out = {{alias}}( x, opts );
    > out.toString()

    See Also
    --------