Statistics in C#
Probability Distributions
Discrete Distributions
Illustrates how to use the classes that represent discrete probability distributions in the Extreme.Statistics.Distributions namespace.
Continuous Distributions
Illustrates how to use the classes that represent continuous probability distributions in the Extreme.Statistics.Distributions namespace.
Analysis of Variance
One-Way Anova
Illustrates how to use the OneWayAnovaModel class to perform a one-way analysis of variance.
Repeated Measures Anova
Illustrates how to use the OneWayRAnovaModel class to perform a one-way analysis of variance with repeated measures.
Two-Way Anova
Illustrates how to use the TwoWayAnovaModel class to perform a two-way analysis of variance.
Regression Analysis
Simple Regression
Illustrates how to perform a simple linear regression using the SimpleRegressionModel class.
Multiple Linear Regression
Illustrates how to use the LinearRegressionModel class to perform a multiple linear regression.
Polynomial Regression
Illustrates how to fit data to polynomials using the PolynomialRegressionModel class.
Logistic Regression
Illustrates how to use the LogisticRegressionModel class to create logistic regression models.
Generalized Linear Models
Illustrates how to use the GeneralizedLinearModel class to compute probit, Poisson and similar regression models.
Time Series Analysis
Simple Time Series
Illustrates how to perform simple operations on time series data using classes in the Extreme.Statistics.TimeSeriesAnalysis namespace.
Variable Transformations
Illustrates how to perform a range of transformations on statistical data.
ARIMA Models
Illustrates how to work with ARIMA time series models using classes in the Extreme.Statistics.TimeSeriesAnalysis namespace.
Multivariate Analysis
Cluster Analysis
Illustrates how to use the classes in the Extreme.Statistics.Multivariate namespace to perform hierarchical clustering and K-means clustering.
Principal Component Analysis (PCA)
Illustrates how to perform a Principal Components Analysis using classes in the Extreme.Statistics.Multivariate namespace.
Factor Analysis (FA)
Illustrates how to perform a Factor Analysis using classes in the Extreme.Statistics.Multivariate namespace.
Hypothesis Tests
Mean Tests
Illustrates how to use various tests for the mean of one or more sanples using classes in the Extreme.Statistics.Tests namespace.
Variance Tests
Illustrates how to perform hypothesis tests involving the standard deviation or variance using classes in our .NET statistical library.
Goodness-Of-Fit Tests
Illustrates how to test for goodness-of-fit using classes in the Extreme.Statistics.Tests namespace.
Homogeneity Of Variances Tests
Illustrates how to test a collection of variables for equal variances using classes in the Extreme.Statistics.Tests namespace.
Non-Parametric Tests
Illustrates how to perform non-parametric tests like the Wilcoxon-Mann-Whitney test and the Kruskal-Wallis test.