TTest Class |
Namespace: Accord.Statistics.Testing
The TTest type exposes the following members.
Name | Description | |
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TTest |
Creates a T-Test.
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TTest(Double, Double, OneSampleHypothesis) |
Tests the null hypothesis that the population mean is equal to a specified value.
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TTest(Double, Double, OneSampleHypothesis) |
Tests the null hypothesis that the population mean is equal to a specified value.
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TTest(Double, Double, Double, Double, OneSampleHypothesis) |
Tests the null hypothesis that the population mean is equal to a specified value.
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TTest(Double, Double, Int32, Double, OneSampleHypothesis) |
Tests the null hypothesis that the population mean is equal to a specified value.
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Name | Description | |
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Analysis |
Gets the power analysis for the test, if available.
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Confidence |
Gets the 95% confidence interval for the EstimatedValue.
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CriticalValue |
Gets the critical value for the current significance level.
(Inherited from HypothesisTestTDistribution.) | |
EstimatedValue |
Gets the estimated parameter value, such as the sample's mean value.
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Hypothesis |
Gets the alternative hypothesis under test. If the test is
Significant, the null hypothesis can be rejected
in favor of this alternative hypothesis.
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HypothesizedValue |
Gets the hypothesized parameter value.
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PValue |
Gets the P-value 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 of the estimated value.
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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.) |
Name | Description | |
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Compute(Double, Double, OneSampleHypothesis) |
Computes the T-test.
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Compute(Int32, Double, Double, Double, OneSampleHypothesis) |
Computes the T-Test.
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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 estimated value
within the given confidence level percentage.
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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(Double) |
Converts a given p-value to a test statistic.
(Overrides HypothesisTestTDistributionPValueToStatistic(Double).) | |
PValueToStatistic(Double, TDistribution, DistributionTail) |
Converts a given p-value to a test statistic.
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StatisticToPValue(Double) |
Converts a given test statistic to a p-value.
(Overrides HypothesisTestTDistributionStatisticToPValue(Double).) | |
StatisticToPValue(Double, TDistribution, DistributionTail) |
Converts a given test statistic to a p-value.
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ToString |
Converts the numeric P-Value of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) | |
ToString(String, IFormatProvider) |
Converts the numeric P-Value of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) |
Name | Description | |
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HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) | |
IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) | |
To(Type) | 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 ExtensionMethods.) |
The one-sample t-test assesses whether the mean of a sample is statistically different from a hypothesized value.
This test supports creating power analyses through its Analysis property.
References:
// Consider a sample generated from a Gaussian // distribution with mean 0.5 and unit variance. double[] sample = { -0.849886940156521, 3.53492346633185, 1.22540422494611, 0.436945126810344, 1.21474290382610, 0.295033941700225, 0.375855651783688, 1.98969760778547, 1.90903448980048, 1.91719241342961 }; // One may rise the hypothesis that the mean of the sample is not // significantly different from zero. In other words, the fact that // this particular sample has mean 0.5 may be attributed to chance. double hypothesizedMean = 0; // Create a T-Test to check this hypothesis TTest test = new TTest(sample, hypothesizedMean, OneSampleHypothesis.ValueIsDifferentFromHypothesis); // Check if the mean is significantly different test.Significant should be true // Now, we would like to test if the sample mean is // significantly greater than the hypothesized zero. // Create a T-Test to check this hypothesis TTest greater = new TTest(sample, hypothesizedMean, OneSampleHypothesis.ValueIsGreaterThanHypothesis); // Check if the mean is significantly larger greater.Significant should be true // Now, we would like to test if the sample mean is // significantly smaller than the hypothesized zero. // Create a T-Test to check this hypothesis TTest smaller = new TTest(sample, hypothesizedMean, OneSampleHypothesis.ValueIsSmallerThanHypothesis); // Check if the mean is significantly smaller smaller.Significant should be false