public void TTestConstructorTest()
{
// Suppose we would like to know the effect of a treatment (such
// as a new drug) in improving the well-being of 9 patients. The
// well-being is measured in a discrete scale, going from 0 to 10.
//
// To do so, we need to register the initial state of each patient
// and then register their state after a given time under treatment.
double[,] patients =
{
// before after
// treatment treatment
/* Patient 1.*/ { 0, 1 },
/* Patient 2.*/ { 6, 5 },
/* Patient 3.*/ { 4, 9 },
/* Patient 4.*/ { 8, 6 },
/* Patient 5.*/ { 1, 6 },
/* Patient 6.*/ { 6, 7 },
/* Patient 7.*/ { 3, 4 },
/* Patient 8.*/ { 8, 7 },
/* Patient 9.*/ { 6, 5 },
};
// Extract the before and after columns
double[] before = patients.GetColumn(0);
double[] after = patients.GetColumn(1);
// Create the paired-sample T-test. Our research hypothesis is
// that the treatment does improve the patient's well-being. So
// we will be testing the hypothesis that the well-being of the
// "before" sample, the first sample, is "smaller" in comparison
// to the "after" treatment group.
PairedTTest test = new PairedTTest(before, after,
TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
bool significant = test.Significant; // false
double pvalue = test.PValue; // ~ 0.165
Assert.IsFalse(significant);
Assert.AreEqual(0.16500, pvalue, 1e-5);
Assert.AreEqual(-1.03712, test.Statistic, 1e-5);
Assert.AreEqual(-0.8888889, test.ObservedDifference, 1e-6);
}
protected override void EndProcessing()
{
var hypo = TestingHelper.GetTwoSampleHypothesis(Alternate);
PairedTTest test;
if (ParameterSetName == "Pipeline")
{
test = new PairedTTest(_data[Sample1Name].ToDoubleArray(), _data[Sample2Name].ToDoubleArray(), hypo);
}
else
{
test = new PairedTTest(Sample1, Sample2, hypo);
}
test.Size = Size;
WriteObject(test);
}
private void Button_Click(object sender, RoutedEventArgs e)
{
List <double> vpop1 = new List <double>();
List <double> vpop2 = new List <double>();
try
{
//Try comma separated instead
var TextScores = pop1.Text.Replace(" ", string.Empty).Split(',').ToList();
foreach (var S in TextScores)
{
vpop1.Add(double.Parse(S));
}
TextScores = pop2.Text.Replace(" ", string.Empty).Split(',').ToList();
foreach (var S in TextScores)
{
vpop2.Add(double.Parse(S));
}
}
catch
{
return;
}
var Hypo = TwoSampleHypothesis.FirstValueIsGreaterThanSecond;
switch (((Button)sender).Content.ToString())
{
case "Dif":
Hypo = TwoSampleHypothesis.ValuesAreDifferent;
break;
case "Less":
Hypo = TwoSampleHypothesis.FirstValueIsSmallerThanSecond;
break;
case "More":
Hypo = TwoSampleHypothesis.FirstValueIsGreaterThanSecond;
break;
default:
break;
}
dynamic test, testWilcoxon;
if (vpop1.Count == vpop2.Count)
{
test = new PairedTTest(vpop1.ToArray(), vpop2.ToArray(), Hypo);
testWilcoxon = new TwoSampleWilcoxonSignedRankTest(vpop1.ToArray(), vpop2.ToArray(), Hypo);
}
else
{
test = new TTest(
vpop1.ToArray(),
vpop2[0],
OneSampleHypothesis.ValueIsSmallerThanHypothesis);
testWilcoxon = new WilcoxonSignedRankTest(
vpop1.ToArray(),
vpop2[0],
OneSampleHypothesis.ValueIsSmallerThanHypothesis);
}
results.Text = "T-Test:\n Significant: " + test.Significant + "\n p-value: " + test.PValue +
"\nMannWhitneyWilcoxon Test:\n Significant: " + testWilcoxon.Significant + "\n p-value: " + testWilcoxon.PValue;
}
public void TTestConstructorTest()
{
// Suppose we would like to know the effect of a treatment (such
// as a new drug) in improving the well-being of 9 patients. The
// well-being is measured in a discrete scale, going from 0 to 10.
//
// To do so, we need to register the initial state of each patient
// and then register their state after a given time under treatment.
double[,] patients =
{
// before after
// treatment treatment
/* Patient 1.*/ { 0, 1 },
/* Patient 2.*/ { 6, 5 },
/* Patient 3.*/ { 4, 9 },
/* Patient 4.*/ { 8, 6 },
/* Patient 5.*/ { 1, 6 },
/* Patient 6.*/ { 6, 7 },
/* Patient 7.*/ { 3, 4 },
/* Patient 8.*/ { 8, 7 },
/* Patient 9.*/ { 6, 5 },
};
// Extract the before and after columns
double[] before = patients.GetColumn(0);
double[] after = patients.GetColumn(1);
// Create the paired-sample T-test. Our research hypothesis is
// that the treatment does improve the patient's well-being. So
// we will be testing the hypothesis that the well-being of the
// "before" sample, the first sample, is "smaller" in comparison
// to the "after" treatment group.
PairedTTest test = new PairedTTest(before, after,
TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
bool significant = test.Significant; // false
double pvalue = test.PValue; // ~ 0.165
Assert.IsFalse(significant);
Assert.AreEqual(0.16500, pvalue, 1e-5);
Assert.AreEqual(-1.03712, test.Statistic, 1e-5);
Assert.AreEqual(-0.8888889, test.ObservedDifference,1e-6);
}
