public void TTest()
{
TTestResult ttest = BasicStatisticalFormulas.TTestEqualVariances(this.AssociatedObject.meandiff.Value, 0.1, this.AssociatedObject.series1, this.AssociatedObject.series2);
this.AssociatedObject.result.Text = "T Value = " + ttest.TValue.ToString() + "\n" +
"T Critical Value one Tail = " + ttest.TCriticalValueOneTail.ToString() + "\n" +
"T Critical value two Tail = " + ttest.TCriticalValueTwoTail.ToString() + "\n" +
"Probability T One Tail = " + ttest.ProbabilityTOneTail.ToString() + "\n" +
"Probability T Two Tail = " + ttest.ProbabilityTTwoTail.ToString() + "\n" +
"First Series Mean = " + ttest.FirstSeriesMean.ToString() + "\n" +
"First Series Variance = " + ttest.FirstSeriesVariance.ToString() + "\n" +
"Second Series Mean = " + ttest.SecondSeriesMean.ToString() + "\n" +
"Second Series Variance =" + ttest.SecondSeriesVariance.ToString() + "\n";
}
private void tryTAndFTest(String mode)
{
if (modeFirst.Equals("") | modeFirst.Equals(mode))
{
modeFirst = mode;
return;
}
TTestResult resultTTest = dummyChart.DataManipulator.Statistics.TTestPaired(0.3, 0.05, modeFirst, mode);
textBox_Results.AppendText("\r\nTTest for " + modeFirst + "\r\nand " + mode + "\r\nis " + resultTTest.TValue);
textBox_Results.AppendText("\r\nProbability: " + resultTTest.ProbabilityTOneTail);
textBox_Results.AppendText("\r\nCritical TValue: " + resultTTest.TCriticalValueOneTail);
FTestResult resultFTest = dummyChart.DataManipulator.Statistics.FTest(0.05, modeFirst, mode);
textBox_Results.AppendText("\r\nFTest for " + modeFirst + "\r\nand " + mode + "\r\nis " + resultFTest.FValue);
textBox_Results.AppendText("\r\nProbability: " + resultFTest.ProbabilityFOneTail);
textBox_Results.AppendText("\r\nCritical FValue: " + resultFTest.FCriticalValueOneTail);
modeFirst = "";
}
public static TTestResult TTest(double[] x, double[] y)
{
TTestResult result = new TTestResult();
// Welch's t-test for two samples
double sumX = 0.0; // calculate means
double sumY = 0.0;
for (int i = 0; i < x.Length; ++i)
{
sumX += x[i];
}
for (int i = 0; i < y.Length; ++i)
{
sumY += y[i];
}
int n1 = x.Length;
int n2 = y.Length;
double meanX = sumX / n1;
double meanY = sumY / n2;
double sumXminusMeanSquared = 0.0; // calculate (sample) variances
double sumYminusMeanSquared = 0.0;
for (int i = 0; i < n1; ++i)
{
sumXminusMeanSquared += (x[i] - meanX) * (x[i] - meanX);
}
for (int i = 0; i < n2; ++i)
{
sumYminusMeanSquared += (y[i] - meanY) * (y[i] - meanY);
}
double varX = sumXminusMeanSquared / (n1 - 1);
double varY = sumYminusMeanSquared / (n2 - 1);
// t statistic
double top = (meanX - meanY);
double bot = Math.Sqrt((varX / n1) + (varY / n2));
double t = top / bot;
// df mildly tricky
// http://www.statsdirect.com/help/default.htm#parametric_methods/unpaired_t.htm
double num = ((varX / n1) + (varY / n2)) *
((varX / n1) + (varY / n2));
double denomLeft = ((varX / n1) * (varX / n1)) / (n1 - 1);
double denomRight = ((varY / n2) * (varY / n2)) / (n2 - 1);
double denom = denomLeft + denomRight;
double df = num / denom;
double p = Student(t, df); // cumulative two-tail density
System.Diagnostics.Debug.WriteLine("mean of x = " + meanX.ToString("F2"));
System.Diagnostics.Debug.WriteLine("mean of y = " + meanY.ToString("F2"));
System.Diagnostics.Debug.WriteLine("t （t-統計）= " + t.ToString("F4"));
System.Diagnostics.Debug.WriteLine("df (自由度) = " + df.ToString("F3"));
System.Diagnostics.Debug.WriteLine("p-value （顯著性） = " + p.ToString("F5"));
result.df = df;
result.p = p;
result.t = t;
result.meanX = meanX;
result.meanY = meanY;
Explain();
return(result);
}
