Sample Class 
Namespace: Meta.Numerics.Statistics
The Sample type exposes the following members.
Name  Description  

Sample 
Initializes a new, empty sample.
 
Sample(IEnumerableDouble) 
Initializes a new sample from a list of values.
 
Sample(Double) 
Initializes a new sample from a list of values.
 
Sample(String) 
Initializes a new, empty sample with the given name.

Name  Description  

CorrectedStandardDeviation 
Gets the Besselcorrected standard deviation.
 
Count 
Gets the number of values in the sample.
 
InterquartileRange 
Gets the interquartile range of sample measurements.
 
IsReadOnly 
Gets a value indicating whether the sample is readonly.
 
Maximum 
Gets the largest value in the sample.
 
Mean 
Gets the sample mean.
 
Median 
Gets the sample median.
 
Minimum 
Gets the smallest value in the sample.
 
Name 
Gets or sets the name of the sample.
 
PopulationMean 
Gets an estimate of the population mean from the sample.
 
PopulationStandardDeviation 
Gets an estimate of the population standard deviation from the sample.
 
PopulationVariance 
Gets an estimate of the population variance from the sample.
 
Skewness 
Gets the sample skewness.
 
StandardDeviation 
Gets the sample standard deviation.
 
Variance 
Gets the sample variance.

Name  Description  

Add(IEnumerableDouble) 
Adds multiple values to the sample.
 
Add(Double) 
Adds a value to the sample.
 
Add(Double) 
Adds multiple values to the sample.
 
CentralMoment 
Computes the given sample central moment.
 
Clear 
Remove all values from the sample.
 
Contains 
Determines whether the sample contains the given value.
 
Copy 
Copies the sample.
 
Equals  Determines whether the specified object is equal to the current object. (Inherited from Object.)  
FisherFTest 
Tests whether the variances of two samples are compatible.
 
GetEnumerator 
Gets an enumerator of sample values.
 
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
InverseLeftProbability 
Gets the sample value corresponding to a given percentile score.
 
KolmogorovSmirnovTest(ContinuousDistribution) 
Tests whether the sample is compatible with the given distribution.
 
KolmogorovSmirnovTest(Sample, Sample) 
Tests whether the sample is compatible with another sample.
 
KruskalWallisTest(Sample) 
Performs a KruskalWallis test on the given samples.
 
KruskalWallisTest(IReadOnlyListSample) 
Performs a KruskalWallis test on the given samples.
 
KuiperTest 
Tests whether the sample is compatible with the given distribution.
 
LeftProbability 
Gets the fraction of values equal to or less than the given value.
 
MannWhitneyTest 
Tests whether one sample median is compatible with another sample median.
 
MaximumLikelihoodFit 
Performs a maximum likelihood fit.
 
OneWayAnovaTest(Sample) 
Performs a oneway analysis of variance (ANOVA).
 
OneWayAnovaTest(IReadOnlyCollectionSample) 
Performs a oneway analysis of variance (ANOVA).
 
PopulationCentralMoment 
Estimates the given population central moment from the sample.
 
PopulationRawMoment 
Estimates the given population raw moment from the sample.
 
RawMoment 
Computes the given sample raw moment.
 
Remove 
Removes a given value from the sample.
 
ShapiroFranciaTest 
Performs a ShapiroFrancia test of normality on the sample.
 
SignTest 
Tests whether the sample median is compatible with the given reference value.
 
StudentTTest(Double) 
Tests whether the sample mean is compatible with the reference mean.
 
StudentTTest(Sample, Sample) 
Tests whether one sample mean is compatible with another sample mean.
 
ToString  Returns a string that represents the current object. (Inherited from Object.)  
Transform 
Transforms all values using a usersupplied function.
 
TwoWayAnovaTest 
Performs a twoway analysis of variance.
 
ZTest 
Performs a ztest.

Name  Description  

CentralMoment 
Computes the given sample central moment.
(Defined by Univariate.)  
CorrectedStandardDeviation 
Computes the Besselcorrected standard deviation.
(Defined by Univariate.)  
Maximum 
Finds the maximum value.
(Defined by Univariate.)  
Mean 
Computes the sample mean.
(Defined by Univariate.)  
Minimum 
Finds the minimum value.
(Defined by Univariate.)  
PopulationCentralMoment 
Estimates the given central moment of the underlying population.
(Defined by Univariate.)  
PopulationMean 
Estimates the mean of the underlying population.
(Defined by Univariate.)  
PopulationRawMoment 
Estimates the given raw moment of the underlying population.
(Defined by Univariate.)  
PopulationStandardDeviation 
Estimates of the standard deviation of the underlying population.
(Defined by Univariate.)  
PopulationVariance 
Estimates of the variance of the underlying population.
(Defined by Univariate.)  
RawMoment 
Computes the given sample raw moment.
(Defined by Univariate.)  
SignTest 
Tests whether the sample median is compatible with the given reference value.
(Defined by Univariate.)  
Skewness 
Computes the sample skewness.
(Defined by Univariate.)  
StandardDeviation 
Computes the sample standard deviation.
(Defined by Univariate.)  
StudentTTest 
Tests whether the sample mean is compatible with the reference mean.
(Defined by Univariate.)  
Variance 
Computes the sample variance.
(Defined by Univariate.)  
ZTest 
Performs a ztest to test whether the given sample is compatible with the given normal reference population.
(Defined by Univariate.) 
A univariate sample is a data set which records one number for each independent observation. For example, data from a study which measured the weight of each subject could be stored in the Sample class. The class offers descriptive statistics for the sample, estimates of descriptive statistics of the underlying population distribution, and statistical tests to compare the sample distribution to other sample distributions or theoretical models.