TwoSampleTTest Class 
Namespace: Accord.Statistics.Testing
The TwoSampleTTest type exposes the following members.
Name  Description  

TwoSampleTTest 
Creates a new twosample TTest.
 
TwoSampleTTest(Double, Double, Boolean, Double, TwoSampleHypothesis) 
Tests whether the means of two samples are different.
 
TwoSampleTTest(Double, Double, Int32, Double, Double, Int32, Boolean, Double, TwoSampleHypothesis) 
Tests whether the means of two samples are different.

Name  Description  

Analysis 
Gets the power analysis for the test, if available.
 
AssumeEqualVariance 
Gets whether the test assumes equal sample variance.
 
Confidence 
Gets the 95% confidence interval for the
ObservedDifference statistic.
 
CriticalValue 
Gets the critical value for the current significance level.
(Inherited from HypothesisTestTDistribution.)  
DegreesOfFreedom 
Gets the degrees of freedom for the test statistic.
 
EstimatedValue1 
Gets the estimated value for the first sample.
 
EstimatedValue2 
Gets the estimated value for the second sample.
 
Hypothesis 
Gets the alternative hypothesis under test. If the test is
Significant, the null hypothesis can be rejected
in favor of this alternative hypothesis.
 
HypothesizedDifference 
Gets the hypothesized difference between the two estimated values.
 
ObservedDifference 
Gets the actual difference between the two estimated values.
 
PValue 
Gets the Pvalue associated with this test.
(Inherited from HypothesisTestTDistribution.)  
Significant 
Gets whether the null hypothesis should be rejected.
(Inherited from HypothesisTestTDistribution.)  
Size 
Gets the significance level for the
test. Default value is 0.05 (5%).
(Inherited from HypothesisTestTDistribution.)  
StandardError 
Gets the standard error for the difference.
 
Statistic 
Gets the test statistic.
(Inherited from HypothesisTestTDistribution.)  
StatisticDistribution 
Gets the distribution associated
with the test statistic.
(Inherited from HypothesisTestTDistribution.)  
Tail 
Gets the test type.
(Inherited from HypothesisTestTDistribution.)  
Variance 
Gets the combined sample variance.

Name  Description  

Compute 
Computes the T Test.
 
Equals  Determines whether the specified object is equal to the current object. (Inherited from Object.)  
Finalize  Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)  
GetConfidenceInterval 
Gets a confidence interval for the ObservedDifference
statistic within the given confidence level percentage.
 
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
MemberwiseClone  Creates a shallow copy of the current Object. (Inherited from Object.)  
OnSizeChanged  Update event. (Overrides HypothesisTestTDistributionOnSizeChanged.)  
PValueToStatistic 
Converts a given pvalue to a test statistic.
(Overrides HypothesisTestTDistributionPValueToStatistic(Double).)  
StatisticToPValue 
Converts a given test statistic to a pvalue.
(Overrides HypothesisTestTDistributionStatisticToPValue(Double).)  
ToString 
Converts the numeric PValue of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.)  
ToString(String, IFormatProvider) 
Converts the numeric PValue of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) 
Name  Description  

HasMethod 
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)  
ToT  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)  
ToT  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by Matrix.) 
The twosample ttest assesses whether the means of two groups are statistically different from each other.
References: