code: public double[] getConfidenceInterval(final double alpha, final Map<?, Double> metricValuesPerDimension) {
          SummaryStatistics differences = new SummaryStatistics();
          for (Double d : metricValuesPerDimension.values()) {
              differences.addValue(d);
          }
          return getConfidenceInterval(alpha, (int) differences.getN() - 1, (int) differences.getN(), differences.getStandardDeviation(), differences.getMean());
      }
docs: Method that takes only one metric as parameter. It is useful when
  comparing more than two metrics (so that a confidence interval is
  computed for each of them), as suggested in [Sakai, 2014]
  
  @param alpha probability of incorrectly rejecting the null hypothesis (1
  - confidence_level)
  @param metricValuesPerDimension one value of the metric for each
  dimension
  @return array with the confidence interval: [mean - margin of error, mean
  + margin of error]