Statistics

mean + (sample) variance

by Danny_Joris

JavaScript

var arr = [1, 2, 3, 5, 10, 25];

var arrLength = arr.length;
var total = 0;
var mean;
var varianceTotal = 0;
var biasedVariance = 0;
var unbiasedVariance = 0;

// array length
document.write("arrLength: " + arrLength + "<br>");
// total
for (var i = 0; i < arrLength; i++) {
    total += arr[i];
}
document.write("total: " + total + "<br>");
// mean
mean = parseFloat(total / arrLength).toFixed(2);
document.write("<strong>mean:</strong> " + mean + "<br>");

// sample variance total
for (var i = 0; i < arrLength; i++) {
    var square;
    var squareSum;
    squareSum = (arr[i] - mean);
    square = squareSum * squareSum;
    square = parseFloat(square).toFixed(2);

    varianceTotal = parseFloat(varianceTotal) + parseFloat(square);
    document.write("square " + i + ": " + square + "<br>");
}
varianceTotal = parseFloat(varianceTotal).toFixed(2);
document.write("variance total: " + varianceTotal + "<br>");

// biased variance (population)
biasedVariance = (varianceTotal / arrLength);
biasedVariance = parseFloat(biasedVariance).toFixed(2);
document.write("<strong>biased variance (population):</strong> " + biasedVariance + "<br>");

// unbiased variance (sample)
unbiasedVariance = (varianceTotal / (arrLength - 1));
unbiasedVariance = parseFloat(unbiasedVariance).toFixed(2);
document.write("<strong>unbiased variance (sample):</strong> " + unbiasedVariance + "<br>");