addDays(days: number): CustomDate {
   var newDay = this.day + days;
   var newMonth = this.month + Math.floor(newDay / 30);
   newDay = newDay % 30;
   var newYear = this.year + Math.floor(newMonth / 12);
   return new CustomDate(newYear, newMonth, newDay);
 }

 static calculateStandardDeviation(samples: number[], mean) {
   var deviation = 0;
   // TODO: use reduce
   samples.forEach(x => deviation += Math.pow(x - mean, 2));
   deviation = deviation / (samples.length);
   deviation = Math.sqrt(deviation);
   return deviation;
 }

 this._printStringRow(this._metricNames.map(metricName => {
   var samples = validSamples.map(measureValues => measureValues.values[metricName]);
   var mean = Statistic.calculateMean(samples);
   var cv = Statistic.calculateCoefficientOfVariation(samples, mean);
   var formattedMean = ConsoleReporter._formatNum(mean);
   // Note: Don't use the unicode character for +- as it might cause
   // hickups for consoles...
   return NumberWrapper.isNaN(cv) ? formattedMean : `${formattedMean}+-${Math.floor(cv)}%`;
 }));

 static calculateRegressionSlope(
     xValues: number[], xMean: number, yValues: number[], yMean: number) {
   // See http://en.wikipedia.org/wiki/Simple_linear_regression
   var dividendSum = 0;
   var divisorSum = 0;
   for (var i = 0; i < xValues.length; i++) {
     dividendSum += (xValues[i] - xMean) * (yValues[i] - yMean);
     divisorSum += Math.pow(xValues[i] - xMean, 2);
   }
   return dividendSum / divisorSum;
 }

 samples.forEach(x => deviation += Math.pow(x - mean, 2));