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kstats is a Kotlin Multiplatform statistics library. It covers descriptive statistics, probability distributions, hypothesis testing, correlation and regression, and sampling — everything needed for quantitative analysis in Kotlin. 
val sample = doubleArrayOf(2.0, 4.0, 4.0, 5.0, 7.0, 9.0)

val summary = sample.describe()
summary.mean              // 5.1667
summary.standardDeviation // 2.4833

val normality = shapiroWilkTest(sample)
normality.pValue          // 0.8933

val fitted = NormalDistribution(mu = summary.mean, sigma = summary.standardDeviation)
fitted.cdf(6.0)           // 0.6335

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Modules

Descriptive Statistics

Mean, median, variance, quantiles, moments, frequency tables, streaming stats, and describe() summaries.

Probability Distributions

18 continuous and 10 discrete distributions with a shared API: pdf/pmf, cdf, quantile, and sampling.

Hypothesis Tests

t-tests, ANOVA, chi-squared, Fisher exact, Mann-Whitney, Wilcoxon, Shapiro-Wilk, and more.

Correlation & Regression

Pearson, Spearman, Kendall tau, partial correlation, matrices, and simple linear regression.

Sampling & Transformation

Ranking, z-score normalization, min-max scaling, binning, bootstrap, and weighted sampling.

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Supported Targets

PlatformTargets
JVMjvm
Androidandroid
Android NativeandroidNativeArm32, androidNativeArm64, androidNativeX86, androidNativeX64
iOSiosX64, iosArm64, iosSimulatorArm64
macOSmacosArm64
LinuxlinuxArm64, linuxX64
WindowsmingwX64
watchOSwatchosArm32, watchosArm64, watchosDeviceArm64, watchosSimulatorArm64
tvOStvosArm64, tvosSimulatorArm64
JSjs (browser, Node.js)
WasmwasmJs, wasmWasi

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Next Steps

Installation

Add the BOM or a single module to a Gradle KTS project.

Quick Start

Run a summary, fit a distribution, and execute a hypothesis test.

A/B Testing

Walk through a complete A/B test with assumption checks and group comparison.
Last modified on April 23, 2026