public void PowerTest1()
{
// Example from http://www.statpower.net/Content/310/Print%20Version%20--%20Power%20for%20the%202-Sample%20Z-Statistic.pdf
double mean1 = 0.5;
double mean2 = 0.0;
double var1 = 0.5;
double var2 = 0.5;
int samples = 25;
TwoSampleZTest test = new TwoSampleZTest(
mean1, var1, samples,
mean2, var2, samples);
TwoSampleZTestPowerAnalysis pa = (TwoSampleZTestPowerAnalysis)test.Analysis;
Assert.AreEqual(0.43, pa.Power, 0.01);
pa.Power = 0.8;
pa.ComputeSamples();
double expectedSamples = 63;
double actualSamples = Math.Ceiling(2 * pa.Samples1);
Assert.AreEqual(expectedSamples, actualSamples);
}
public void TestMethod1()
{
var concurrent = new ConcurrentPrimes();
concurrent.Init(cMinPrime, cMaxPrime, cDegreeConcurrency);
PerformanceResult concResult = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() => concurrent.Execute()));
Console.WriteLine(cResultFormat + " with concurrent collection.", cMinPerfIterations,
concResult.TotalMilliseconds,
concResult.TotalSeconds);
var plinqed = new PlinqPrimes();
plinqed.Init(cMinPrime, cMaxPrime, cDegreeConcurrency);
PerformanceResult pResult = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() => plinqed.Execute()));
Console.WriteLine(cResultFormat + " with plinq.", cMinPerfIterations, pResult.TotalMilliseconds,
pResult.TotalSeconds);
var comparison = new TwoSampleZTest(pResult.DescriptiveResult, concResult.DescriptiveResult, 0.0,
TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
Console.WriteLine(concResult.ToString());
Console.WriteLine(pResult.ToString());
Assert.IsTrue(comparison.Significant);
Assert.AreEqual(concurrent.Primes.Count,plinqed.Primes.Count);
}
public void CompareMethods()
{
PerformanceResult resultWith = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() => FuncWithLookup()));
Console.WriteLine(cResultFormat + " with lookup.", cMinPerfIterations, resultWith.TotalMilliseconds,
resultWith.TotalSeconds);
PerformanceResult resultWithout = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() =>
{
var payids = (from payment in _bigList
select payment.PayId).Distinct();
var myStuff = (from payid in payids.AsParallel()
select new
{
PayId = payid,
coverages =
string.Join(", ", _bigList.Where(x => x.PayId == payid).Select(x => x.CategoryCode)),
total = _bigList.Where(x => x.PayId == payid).Select(x => x.PaymentAmount).Sum()
}).ToList();
var myList = myStuff.ToList();
}));
Console.WriteLine(cResultFormat + " without lookup.", cMinPerfIterations, resultWithout.TotalMilliseconds,
resultWithout.TotalSeconds);
var comparison = new TwoSampleZTest(resultWith.DescriptiveResult, resultWithout.DescriptiveResult, 0.0, TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
Assert.IsTrue(comparison.Significant);
}
public void TwoSampleZTestConstructorTest()
{
Accord.Math.Tools.SetupGenerator(0);
double[] samples1 = new Accord.Statistics.Distributions.Univariate
.NormalDistribution(29.8, 4.0).Generate(200);
double[] samples2 = new Accord.Statistics.Distributions.Univariate
.NormalDistribution(34.7, 5.0).Generate(250);
TwoSampleZTest actual = new TwoSampleZTest(samples1, samples2);
double mean1 = Accord.Statistics.Tools.Mean(samples1);
double mean2 = Accord.Statistics.Tools.Mean(samples2);
double var1 = Accord.Statistics.Tools.Variance(samples1);
double var2 = Accord.Statistics.Tools.Variance(samples2);
int n1 = samples1.Length;
int n2 = samples2.Length;
TwoSampleZTest expected = new TwoSampleZTest(mean1, var1, n1, mean2, var2, n2);
Assert.AreEqual(expected.EstimatedValue1, actual.EstimatedValue1);
Assert.AreEqual(expected.EstimatedValue2, actual.EstimatedValue2);
Assert.AreEqual(expected.StandardError, actual.StandardError);
Assert.AreEqual(expected.Statistic, actual.Statistic);
Assert.IsTrue(actual.Significant);
}
public void TwoSampleZTestConstructorTest()
{
Accord.Math.Tools.SetupGenerator(0);
double[] samples1 = new Accord.Statistics.Distributions.Univariate
.NormalDistribution(29.8, 4.0).Generate(200);
double[] samples2 = new Accord.Statistics.Distributions.Univariate
.NormalDistribution(34.7, 5.0).Generate(250);
TwoSampleZTest actual = new TwoSampleZTest(samples1, samples2);
double mean1 = Accord.Statistics.Tools.Mean(samples1);
double mean2 = Accord.Statistics.Tools.Mean(samples2);
double var1 = Accord.Statistics.Tools.Variance(samples1);
double var2 = Accord.Statistics.Tools.Variance(samples2);
int n1 = samples1.Length;
int n2 = samples2.Length;
TwoSampleZTest expected = new TwoSampleZTest(mean1, var1, n1, mean2, var2, n2);
Assert.AreEqual(expected.EstimatedValue1, actual.EstimatedValue1);
Assert.AreEqual(expected.EstimatedValue2, actual.EstimatedValue2);
Assert.AreEqual(expected.StandardError, actual.StandardError);
Assert.AreEqual(expected.Statistic, actual.Statistic);
Assert.IsTrue(actual.Significant);
}
public void TwoSampleZTestConstructorTest2()
{
// Example from http://www.stat.purdue.edu/~tlzhang/stat511/chapter9_1.pdf
double mean1 = 29.8;
double var1 = System.Math.Pow(4.0, 2);
int samples1 = 20;
double mean2 = 34.7;
double var2 = System.Math.Pow(5.0, 2);
int samples2 = 25;
TwoSampleZTest target = new TwoSampleZTest(
mean1, var1, samples1,
mean2, var2, samples2);
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(-3.66, target.Statistic, 0.01);
var range = target.GetConfidenceInterval(0.99);
Assert.AreEqual(-8.36, range.Min, 0.01);
Assert.AreEqual(-1.44, range.Max, 0.01);
Assert.IsTrue(target.Significant);
target.Size = 0.01;
Assert.IsTrue(target.Significant);
}
public void SampleSizeTest1()
{
// Example from http://udel.edu/~mcdonald/statttest.html
double mean1 = 3.2;
double mean2 = 0;
double var1 = System.Math.Pow(4.0, 2);
double var2 = System.Math.Pow(4.3, 2);
double alpha = 0.05;
double power = 0.80;
TwoSampleZTest test = new TwoSampleZTest(mean1, var1, 10, mean2, var2, 10,
alternate: TwoSampleHypothesis.ValuesAreDifferent);
var target = (TwoSampleZTestPowerAnalysis)test.Analysis.Clone();
target.Power = power;
target.Size = alpha;
target.ComputeSamples(1);
double actual = Math.Ceiling(target.Samples1);
double expected = 27;
Assert.AreEqual(expected, actual, 1e-3);
}
/// <summary>
/// Creates a new <see cref="ZTestPowerAnalysis"/>.
/// </summary>
///
/// <param name="test">The test to create the analysis for.</param>
///
public ZTestPowerAnalysis(TwoSampleZTest test)
: base(test.Tail)
{
this.Power = test.Analysis.Power;
this.Size = test.Analysis.Size;
this.Effect = test.Analysis.Effect;
this.Samples = test.Analysis.Samples;
}
/// <summary>
/// Creates a new <see cref="ZTestPowerAnalysis"/>.
/// </summary>
///
/// <param name="test">The test to create the analysis for.</param>
///
public ZTestPowerAnalysis(TwoSampleZTest test)
: base(test.Tail)
{
this.Power = test.Analysis.Power;
this.Size = test.Analysis.Size;
this.Effect = test.Analysis.Effect;
this.Samples = test.Analysis.Samples;
}
public void TwoSampleZTestConstructorTest3()
{
// Example from Larser & Farber, Elementary Statistics: Picturing the world
/*
* A high school math teacher claims that students in her class
* will score higher on the math portion of the ACT then students
* in a colleague’s math class. The mean ACT math score for 49
* students in her class is 22.1 and the standard deviation is 4.8.
* The mean ACT math score for 44 of the colleague’s students is
* 19.8 and the standard deviation is 5.4. At a = 0.10, can the
* teacher’s claim be supported?
*/
double mean1 = 22.1;
double var1 = System.Math.Pow(4.8, 2);
int samples1 = 49;
double mean2 = 19.8;
double var2 = System.Math.Pow(5.4, 2);
int samples2 = 44;
{
TwoSampleZTest target = new TwoSampleZTest(
mean1, var1, samples1,
mean2, var2, samples2,
alternate: TwoSampleHypothesis.FirstValueIsGreaterThanSecond);
target.Size = 0.10;
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(1.0644, target.StandardError, 0.0001);
Assert.AreEqual(2.161, target.Statistic, 0.001);
Assert.IsTrue(target.Significant);
}
{
TwoSampleZTest target = new TwoSampleZTest(
mean2, var2, samples2,
mean1, var1, samples1,
alternate: TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
target.Size = 0.10;
Assert.AreEqual(mean2, target.EstimatedValue1);
Assert.AreEqual(mean1, target.EstimatedValue2);
Assert.AreEqual(1.0644, target.StandardError, 0.0001);
Assert.AreEqual(-2.161, target.Statistic, 0.001);
Assert.IsTrue(target.Significant);
}
}
public GeneralHypothesisTest(string firstLabel, DescriptiveResult sample1, string secondLabel,
DescriptiveResult sample2, double hypothesizedDifference = 0,
TwoSampleHypothesis alternate = TwoSampleHypothesis.ValuesAreDifferent)
{
int samples1 = sample1.Count;
int samples2 = sample2.Count;
HypothesizedDifference = Math.Abs(hypothesizedDifference);
var s1 = new SampleInfo
{
Name = firstLabel,
Count = sample1.Count,
Mean = sample1.Mean,
StdDev = sample1.StdDev
};
var s2 = new SampleInfo
{
Name = secondLabel,
Count = sample2.Count,
Mean = sample2.Mean,
StdDev = sample2.StdDev
};
Result = new ComparisonResult
{
FirstSample = s1,
SecondSample = s2,
Hypothesis = alternate,
HypothesizedDifference = HypothesizedDifference
};
if (samples1 < 30 || samples2 < 30)
{
_tTest = new TwoSampleTTest(sample1, sample2, false, HypothesizedDifference, alternate);
Result.Confidence = _tTest.Confidence;
Result.ObservedDifference = _tTest.ObservedDifference;
Result.Significant = _tTest.Significant;
Result.Size = _tTest.Size;
Result.StandardError = _tTest.StandardError;
}
else
{
_zTest = new TwoSampleZTest(sample1, sample2, HypothesizedDifference, alternate);
Result.Confidence = _zTest.Confidence;
Result.ObservedDifference = _zTest.ObservedDifference;
Result.Significant = _zTest.Significant;
Result.Size = _zTest.Size;
Result.StandardError = _zTest.StandardError;
}
}
public void ExtraLargeIntKey()
{
InitIntData(cXLargeTableSize);
RunIntTests();
var comparison = new TwoSampleZTest(_dictResult.DescriptiveResult, _tableResult.DescriptiveResult, 0.0,
TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
Console.WriteLine(_dictResult.ToString());
Console.WriteLine(_tableResult.ToString());
Assert.IsTrue(comparison.Significant);
}
public TwoSampleHypothesisTestResult TestHypothesis(IEnumerable <double> sample1, IEnumerable <double> sample2, double hypothesizedDifference,
TwoSampleHypothesis alternateHypothesis, double alpha)
{
var test = new TwoSampleZTest(
sample1.ToArray(),
sample2.ToArray(),
hypothesizedDifference: hypothesizedDifference,
alternate: alternateHypothesis);
test.Size = alpha;
return(new TwoSampleHypothesisTestResult(
test.Significant,
test.GetConfidenceInterval(1 - alpha),
test.ObservedDifference));
}
public void ExtraLargeIntKeyvStringKey()
{
InitSIData(cXLargeTableSize);
RunSITests();
var comparison = new TwoSampleZTest(_dictResult.DescriptiveResult, _tableResult.DescriptiveResult, 0.0,
TwoSampleHypothesis.ValuesAreDifferent);
Console.WriteLine(_dictResult.ToString());
Console.WriteLine(_tableResult.ToString());
// Interesting view of "significant" here. A test with this many runs is almost always significant
// statistically. But another read of "significant" is that sometimes this shows as a significant diff
// and sometimes not. Depends on the run.
Assert.IsFalse(comparison.Significant);
}
public void TestMethod1()
{
PerformanceResult boxResult = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() =>
{
if (_boxList.Count < (cMinPerfIterations >> 2))
{
_boxList.Add(_rng.Next());
}
else
{
int i = _rng.Next(0, _boxList.Count - 1);
var r = (int) _boxList[i];
_boxList.RemoveAt(i);
}
}));
Console.WriteLine(cResultFormat + " with boxing.", cMinPerfIterations, boxResult.TotalMilliseconds,
boxResult.TotalSeconds);
PerformanceResult noboxResult = PerformancePatterns.RunPerformanceTest(cMinPerfIterations,
(() =>
{
if (_noboxList.Count < (cMinPerfIterations >> 2))
{
_noboxList.Add(_rng.Next());
}
else
{
int i = _rng.Next(0, _noboxList.Count - 1);
int r = _noboxList[i];
_noboxList.RemoveAt(i);
}
}));
Console.WriteLine(cResultFormat + " with generic collection.", cMinPerfIterations,
noboxResult.TotalMilliseconds, noboxResult.TotalSeconds);
var comparison = new TwoSampleZTest(noboxResult.DescriptiveResult, boxResult.DescriptiveResult, 0.0,
TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
Console.WriteLine(noboxResult.ToString());
Console.WriteLine(boxResult.ToString());
Assert.IsTrue(comparison.Significant);
}
public void Test1()
{
PerformanceResult contentionResult = PerformancePatterns.RunConcurrentPerformanceTest(cMinPerfIterations,
cDegreeConcurrency, (() =>
{
lock (_collectionLock)
{
int v = _rng.Next(1, cMinPerfIterations);
if (_bigList.Count > (cMinPerfIterations >> 2))
{
var s = _bigList[v%_bigList.Count];
_bigList.RemoveAt(v % _bigList.Count);
}
else
{
_bigList.Add(v);
}
}
}));
Console.WriteLine(cResultFormat + " with contention.", cMinPerfIterations, contentionResult.TotalMilliseconds, contentionResult.TotalSeconds);
PerformanceResult concurrentResult = PerformancePatterns.RunConcurrentPerformanceTest(cMinPerfIterations,
cDegreeConcurrency, (() =>
{
int v = _rng.Next(1, cMinPerfIterations);
if (_concurrentQ.Count > (cMinPerfIterations >> 2))
{
var s = _concurrentQ.Take();
}
else
{
_concurrentQ.Add(v);
}
}));
Console.WriteLine(cResultFormat + " with concurrent collection.", cMinPerfIterations, concurrentResult.TotalMilliseconds, concurrentResult.TotalSeconds);
var comparison = new TwoSampleZTest(concurrentResult.DescriptiveResult, contentionResult.DescriptiveResult, 0.0, TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
Console.WriteLine(concurrentResult.ToString());
Console.WriteLine(contentionResult.ToString());
Assert.IsTrue(comparison.Significant);
}
public void TwoSampleZTestConstructorTest1()
{
// Example from http://www.stat.ucla.edu/~cochran/stat10/winter/lectures/lect21.html
double mean1 = 9.78;
double var1 = System.Math.Pow(4.05, 2);
int samples1 = 900;
double mean2 = 15.10;
double var2 = System.Math.Pow(4.28, 2);
int samples2 = 1000;
TwoSampleZTest target = new TwoSampleZTest(mean1, var1, samples1, mean2, var2, samples2);
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(0.19, target.StandardError, 0.005);
Assert.AreEqual(-28, target.Statistic, 0.5);
Assert.IsTrue(target.Significant);
}
public SamplesRequirement GetSampleSizeRequirement(BenchmarkResults.BeforeAndAfter basedOnPreliminaryResults)
{
if (basedOnPreliminaryResults.Baseline.ResultStatistics.N < 30 ||
basedOnPreliminaryResults.Treatment.ResultStatistics.N < 30)
{
throw new InvalidOperationException(
"Too few samples for Z test - please use T test");
}
var test = new TwoSampleZTest(
basedOnPreliminaryResults.Baseline.GetAverageNanosecondsForResultRuns(),
basedOnPreliminaryResults.Treatment.GetAverageNanosecondsForResultRuns(),
// TODO: P1 - Doing the tests separately like this and doing one tailed is not correct
// but achieving the call syntax we want with the semantics statistics needs is hard :(
// The specific problem is that the desired significance might not be achieved based on how this is done
alternate: TwoSampleHypothesis.ValuesAreDifferent);
Func <BaseTwoSamplePowerAnalysis, int> getSampleSizeForSample1 = analysis => (int)Math.Min(int.MaxValue, Math.Ceiling(analysis.Samples1));
// WORK AROUND FOR BUG IN ACCORD
{
// This was a weirdness in the Accord library - looks like a bug. We are going to work around it but validate it here in case it changes in the future.
var originalAnalysis = test.Analysis.Clone() as TwoSampleZTestPowerAnalysis;
var newAnalysis = test.Analysis as TwoSampleZTestPowerAnalysis;
newAnalysis.Power = 0.80;
newAnalysis.ComputeSamples();
var smallerPower = originalAnalysis.Power < newAnalysis.Power ? originalAnalysis : newAnalysis;
var largerPower = smallerPower == newAnalysis ? originalAnalysis : newAnalysis;
if (largerPower.Samples1 < smallerPower.Samples1)
{
// Not expected, but is the bug we are working around
if (largerPower.TotalSamples > smallerPower.Samples1)
{
// Bug validated, our work around is okay
getSampleSizeForSample1 = analysis => (int)Math.Min(int.MaxValue, Math.Ceiling(analysis.TotalSamples));
}
else
{
throw new InvalidOperationException(
"Larger power resulted in smaller sample size needed? Impossible.");
}
}
else
{
getSampleSizeForSample1 = analysis => (int)Math.Min(int.MaxValue, Math.Ceiling(analysis.TotalSamples));
var version = FileVersionInfo.GetVersionInfo(typeof(BaseTwoSamplePowerAnalysis).Assembly.Location);
if (version.FileMajorPart == 3 && version.FileMinorPart <= 8)
{
// Known version
}
else
{
throw new InvalidOperationException(
$"It's possible you just need a lot more samples, but it's also possible our work around for a bug in Accord is no longer needed. Gotta check this! {smallerPower.Samples1} {largerPower.Samples1}");
}
}
}
// WORK AROUND FOR BUG IN ACCORD
// The difference standard deviation
var standardDeviation = test.StandardError * Math.Sqrt(basedOnPreliminaryResults.Baseline.ResultStatistics.N);
var size4 = TwoSampleZTestPowerAnalysis.GetSampleSize(
// TODO: Does this delta need to be minimumDetectableDifferenceDesired, or do we use the observed difference?
delta: test.ObservedDifference,
power: this.testStatisticalPower,
alpha: this.alpha,
// TODO: P1 - Does the direction here matter?
hypothesis: TwoSampleHypothesis.ValuesAreDifferent,
standardDeviation: standardDeviation);
var n1 = getSampleSizeForSample1(size4);
return(new SamplesRequirement(
(int)Math.Min(int.MaxValue, n1),
(int)Math.Min(int.MaxValue, n1)));
}
public void TwoSampleZTestConstructorTest1()
{
// Example from http://www.stat.ucla.edu/~cochran/stat10/winter/lectures/lect21.html
double mean1 = 9.78;
double var1 = System.Math.Pow(4.05, 2);
int samples1 = 900;
double mean2 = 15.10;
double var2 = System.Math.Pow(4.28, 2);
int samples2 = 1000;
TwoSampleZTest target = new TwoSampleZTest(mean1, var1, samples1, mean2, var2, samples2);
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(0.19, target.StandardError, 0.005);
Assert.AreEqual(-28, target.Statistic, 0.5);
Assert.IsTrue(target.Significant);
}
public void SampleSizeTest1()
{
// Example from http://udel.edu/~mcdonald/statttest.html
double mean1 = 3.2;
double mean2 = 0;
double var1 = System.Math.Pow(4.0, 2);
double var2 = System.Math.Pow(4.3, 2);
double alpha = 0.05;
double power = 0.80;
TwoSampleZTest test = new TwoSampleZTest(mean1, var1, 10, mean2, var2, 10,
alternate: TwoSampleHypothesis.ValuesAreDifferent);
var target = (TwoSampleZTestPowerAnalysis)test.Analysis.Clone();
target.Power = power;
target.Size = alpha;
target.ComputeSamples(1);
double actual = Math.Ceiling(target.Samples1);
double expected = 27;
Assert.AreEqual(expected, actual, 1e-3);
}
public void PowerTest1()
{
// Example from http://www.statpower.net/Content/310/Print%20Version%20--%20Power%20for%20the%202-Sample%20Z-Statistic.pdf
double mean1 = 0.5;
double mean2 = 0.0;
double var1 = 0.5;
double var2 = 0.5;
int samples = 25;
TwoSampleZTest test = new TwoSampleZTest(
mean1, var1, samples,
mean2, var2, samples);
TwoSampleZTestPowerAnalysis pa = (TwoSampleZTestPowerAnalysis)test.Analysis;
Assert.AreEqual(0.43, pa.Power, 0.01);
pa.Power = 0.8;
pa.ComputeSamples();
double expectedSamples = 63;
double actualSamples = Math.Ceiling(2 * pa.Samples1);
Assert.AreEqual(expectedSamples, actualSamples);
}
public void TwoSampleZTestConstructorTest3()
{
// Example from Larser & Farber, Elementary Statistics: Picturing the world
/*
* A high school math teacher claims that students in her class
* will score higher on the math portion of the ACT then students
* in a colleague’s math class. The mean ACT math score for 49
* students in her class is 22.1 and the standard deviation is 4.8.
* The mean ACT math score for 44 of the colleague’s students is
* 19.8 and the standard deviation is 5.4. At a = 0.10, can the
* teacher’s claim be supported?
*/
double mean1 = 22.1;
double var1 = System.Math.Pow(4.8, 2);
int samples1 = 49;
double mean2 = 19.8;
double var2 = System.Math.Pow(5.4, 2);
int samples2 = 44;
{
TwoSampleZTest target = new TwoSampleZTest(
mean1, var1, samples1,
mean2, var2, samples2,
alternate: TwoSampleHypothesis.FirstValueIsGreaterThanSecond);
target.Size = 0.10;
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(1.0644, target.StandardError, 0.0001);
Assert.AreEqual(2.161, target.Statistic, 0.001);
Assert.IsTrue(target.Significant);
}
{
TwoSampleZTest target = new TwoSampleZTest(
mean2, var2, samples2,
mean1, var1, samples1,
alternate: TwoSampleHypothesis.FirstValueIsSmallerThanSecond);
target.Size = 0.10;
Assert.AreEqual(mean2, target.EstimatedValue1);
Assert.AreEqual(mean1, target.EstimatedValue2);
Assert.AreEqual(1.0644, target.StandardError, 0.0001);
Assert.AreEqual(-2.161, target.Statistic, 0.001);
Assert.IsTrue(target.Significant);
}
}
public void TwoSampleZTestConstructorTest2()
{
// Example from http://www.stat.purdue.edu/~tlzhang/stat511/chapter9_1.pdf
double mean1 = 29.8;
double var1 = System.Math.Pow(4.0, 2);
int samples1 = 20;
double mean2 = 34.7;
double var2 = System.Math.Pow(5.0, 2);
int samples2 = 25;
TwoSampleZTest target = new TwoSampleZTest(
mean1, var1, samples1,
mean2, var2, samples2);
Assert.AreEqual(mean1, target.EstimatedValue1);
Assert.AreEqual(mean2, target.EstimatedValue2);
Assert.AreEqual(-3.66, target.Statistic, 0.01);
var range = target.GetConfidenceInterval(0.99);
Assert.AreEqual(-8.36, range.Min, 0.01);
Assert.AreEqual(-1.44, range.Max, 0.01);
Assert.IsTrue(target.Significant);
target.Size = 0.01;
Assert.IsTrue(target.Significant);
}
