/// @return double t-test confidence level with data accumulated /// in the supplied moments. /// The variance of both sets is assumed to be the same. /// @param m DhbStatistics.StatisticalMoments public double TConfidenceLevel(StatisticalMoments m) { int dof = (int)(Count + m.Count - 2); double sbar = Math.Sqrt((UnnormalizedVariance + m.UnnormalizedVariance) / dof); StudentDistribution tDistr = new StudentDistribution(dof); return(tDistr.ConfidenceLevel((Average - m.Average) / (sbar * Math.Sqrt(1.0 / Count + 1.0 / m.Count)))); }
/// @return double t-test confidence level with data accumulated /// in the supplied moments. /// Approximation for the case where the variance of both sets may /// differ. /// @param m DhbStatistics.StatisticalMoments public double TApproximateConfidenceLevel(StatisticalMoments m) { StudentDistribution tDistr = new StudentDistribution( (int)(Count + m.Count - 2)); return(tDistr.ConfidenceLevel((Average / StandardDeviation - m.Average / m.StandardDeviation) / Math.Sqrt(1 / Count + 1 / m.Count))); }