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import mean from "./mean";
/** * [Skewness](http://en.wikipedia.org/wiki/Skewness) is * a measure of the extent to which a probability distribution of a * real-valued random variable "leans" to one side of the mean. * The skewness value can be positive or negative, or even undefined. * * Implementation is based on the adjusted Fisher-Pearson standardized * moment coefficient, which is the version found in Excel and several * statistical packages including Minitab, SAS and SPSS. * * @since 4.1.0 * @param {Array<number>} x a sample of 3 or more data points * @returns {number} sample skewness * @throws {Error} if x has length less than 3 * @example * sampleSkewness([2, 4, 6, 3, 1]); // => 0.590128656384365 */function sampleSkewness(x) {    if (x.length < 3) {        throw new Error("sampleSkewness requires at least three data points");    }
    const meanValue = mean(x);    let tempValue;    let sumSquaredDeviations = 0;    let sumCubedDeviations = 0;
    for (let i = 0; i < x.length; i++) {        tempValue = x[i] - meanValue;        sumSquaredDeviations += tempValue * tempValue;        sumCubedDeviations += tempValue * tempValue * tempValue;    }
    // this is Bessels' Correction: an adjustment made to sample statistics    // that allows for the reduced degree of freedom entailed in calculating    // values from samples rather than complete populations.    const besselsCorrection = x.length - 1;
    // Find the mean value of that list    const theSampleStandardDeviation = Math.sqrt(        sumSquaredDeviations / besselsCorrection    );
    const n = x.length;    const cubedS = Math.pow(theSampleStandardDeviation, 3);
    return (n * sumCubedDeviations) / ((n - 1) * (n - 2) * cubedS);}
export default sampleSkewness;