differencesProbability = Statistics.FProbability(tval * tval, 1, (int) count - 1);
if (count > 1) { differencesProbability = Statistics.FProbability(tval * tval, 1, (int) count - 1); } else differencesProbability = 1;
  public void calculateDerived() {    xStats.calculateDerived();    yStats.calculateDerived();    differencesStats.calculateDerived();    correlation = Double.NaN;    if (!Double.isNaN(xStats.stdDev) && !Double.isNaN(yStats.stdDev)	&& !Utils.eq(xStats.stdDev, 0)) {      double slope = (xySum - xStats.sum * yStats.sum / count)	/ (xStats.sumSq - xStats.sum * xStats.mean);      if (!Utils.eq(yStats.stdDev, 0)) {	correlation = slope * xStats.stdDev / yStats.stdDev;      } else {	correlation = 1.0;      }    }    if (Utils.gr(differencesStats.stdDev, 0)) {      double tval = differencesStats.mean	* Math.sqrt(count)	/ differencesStats.stdDev;      differencesProbability = Statistics.FProbability(tval * tval, 1,						       (int) count - 1);    } else {      if (differencesStats.sumSq == 0) {	differencesProbability = 1.0;      } else {	differencesProbability = 0.0;      }    }    differencesSignificance = 0;    if (differencesProbability <= sigLevel) {      if (xStats.mean > yStats.mean) {	differencesSignificance = 1;      } else {	differencesSignificance = -1;      }    }  }