| 1 | import { Math } from 'angular2/src/facade/math';
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| 2 | export class Statistic {
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| 3 | static calculateCoefficientOfVariation(sample, mean) {
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| 4 | return Statistic.calculateStandardDeviation(sample, mean) / mean * 100;
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| 5 | }
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| 6 | static calculateMean(samples) {
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| 7 | var total = 0;
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| 8 | // TODO: use reduce
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| 9 | samples.forEach(x => total += x);
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| 10 | return total / samples.length;
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| 11 | }
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| 12 | static calculateStandardDeviation(samples, mean) {
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| 13 | var deviation = 0;
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| 14 | // TODO: use reduce
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| 15 | samples.forEach(x => deviation += Math.pow(x - mean, 2));
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| 16 | deviation = deviation / (samples.length);
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| 17 | deviation = Math.sqrt(deviation);
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| 18 | return deviation;
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| 19 | }
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| 20 | static calculateRegressionSlope(xValues, xMean, yValues, yMean) {
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| 21 | // See http://en.wikipedia.org/wiki/Simple_linear_regression
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| 22 | var dividendSum = 0;
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| 23 | var divisorSum = 0;
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| 24 | for (var i = 0; i < xValues.length; i++) {
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| 25 | dividendSum += (xValues[i] - xMean) * (yValues[i] - yMean);
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| 26 | divisorSum += Math.pow(xValues[i] - xMean, 2);
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| 27 | }
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| 28 | return dividendSum / divisorSum;
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| 29 | }
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| 30 | }
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