ZTest Class |
Namespace: Accord.Statistics.Testing
The ZTest type exposes the following members.
Name | Description | |
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ZTest |
Constructs a T-Test.
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ZTest(Double, OneSampleHypothesis) |
Constructs a Z test.
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ZTest(Double, Double, OneSampleHypothesis) |
Constructs a Z test.
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ZTest(Double, Double, Double, OneSampleHypothesis) |
Constructs a Z test.
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ZTest(Double, Double, Int32, Double, OneSampleHypothesis) |
Constructs a Z test.
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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 value, such as the mean estimated from a sample.
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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 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, OneSampleHypothesis) |
Computes the Z test.
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Compute(Double, Double, Double, OneSampleHypothesis) |
Computes the Z 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 EstimatedValue
statistic 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, 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, 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 term Z-test is often used to refer specifically to the one-sample location test comparing the mean of a set of measurements to a given constant. Due to the central limit theorem, many test statistics are approximately normally distributed for large samples. Therefore, many statistical tests can be performed as approximate Z-tests if the sample size is large.
If the test is Significant, the null hypothesis can be rejected in favor of the alternate hypothesis specified at the creation of the test.
This test supports creating power analyses through its Analysis property.
References:
This example has been gathered from the Wikipedia's page about the Z-Test, available from: http://en.wikipedia.org/wiki/Z-test
Suppose there is a text comprehension test being run across a given demographic region. The mean score of the population from this entire region are around 100 points, with a standard deviation of 12 points.
There is a local school, however, whose 55 students attained an average score in the test of only about 96 points. Would their scores be surprisingly that low, or could this event have happened due to chance?
// So we would like to check that a sample of // 55 students with a mean score of 96 points: int sampleSize = 55; double sampleMean = 96; // Was expected to have happened by chance in a population with // an hypothesized mean of 100 points and standard deviation of // about 12 points: double standardDeviation = 12; double hypothesizedMean = 100; // So we start by creating the test: ZTest test = new ZTest(sampleMean, standardDeviation, sampleSize, hypothesizedMean, OneSampleHypothesis.ValueIsSmallerThanHypothesis); // Now, we can check whether this result would be // unlikely under a standard significance level: bool significant = test.Significant; // We can also check the test statistic and its P-Value double statistic = test.Statistic; double pvalue = test.PValue;