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Crate numra_stats

Crate numra_stats 

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Expand description

Statistics and probability distributions for Numra.

This crate provides:

  • Distributions: Normal, Uniform, Exponential, Gamma, Beta, Chi-squared, Student’s t, F, Poisson, Binomial, Log-normal
  • Descriptive statistics: mean, variance, std_dev, median, percentile, skewness, kurtosis, covariance, covariance_matrix
  • Hypothesis testing: t-tests (one-sample, two-sample, paired), chi-squared, Kolmogorov-Smirnov, one-way ANOVA
  • Regression: linear, multiple linear, polynomial
  • Correlation: Pearson, Spearman

Author: Moussa Leblouba Date: 9 February 2026 Modified: 2 May 2026

Re-exports§

pub use error::StatsError;
pub use distributions::ContinuousDistribution;
pub use distributions::DiscreteDistribution;
pub use distributions::BetaDist;
pub use distributions::Binomial;
pub use distributions::ChiSquared;
pub use distributions::Exponential;
pub use distributions::FDist;
pub use distributions::GammaDist;
pub use distributions::LogNormal;
pub use distributions::Normal;
pub use distributions::Poisson;
pub use distributions::StudentT;
pub use distributions::Uniform;
pub use descriptive::covariance;
pub use descriptive::covariance_matrix;
pub use descriptive::kurtosis;
pub use descriptive::mean;
pub use descriptive::median;
pub use descriptive::percentile;
pub use descriptive::skewness;
pub use descriptive::std_dev;
pub use descriptive::variance;
pub use hypothesis::anova_oneway;
pub use hypothesis::chi2_test;
pub use hypothesis::ks_test;
pub use hypothesis::ttest_1samp;
pub use hypothesis::ttest_ind;
pub use hypothesis::ttest_rel;
pub use hypothesis::TestResult;
pub use regression::linregress;
pub use regression::multiple_linregress;
pub use regression::polyfit;
pub use regression::RegressionResult;
pub use correlation::pearson_r;
pub use correlation::spearman_r;

Modules§

correlation
Correlation analysis: Pearson, Spearman.
descriptive
Descriptive statistics: mean, variance, standard deviation, percentiles, etc.
distributions
Probability distribution traits and implementations.
error
Error types for statistical computations.
hypothesis
Hypothesis testing: t-tests, chi-squared, Kolmogorov-Smirnov, ANOVA.
regression
Linear regression, multiple regression, and polynomial fitting.