Hypothesis Tests
A comprehensive Julia package implementing a wide range of statistical hypothesis tests for data analysis.
What is Hypothesis Tests?
HypothesisTests.jl is a Julia package that implements a wide range of statistical hypothesis tests for data analysis. It provides tools for performing parametric tests (like t-tests) and non-parametric tests (like Mann-Whitney U test) to evaluate statistical significance. The package calculates p-values, confidence intervals, and test statistics to support rigorous statistical inference.
Data scientists, researchers, and statisticians working in Julia who need to perform hypothesis testing as part of their data analysis workflows.
It offers a comprehensive, native Julia implementation of statistical tests with a clean API, eliminating the need to interface with external statistical software. The package integrates seamlessly with the JuliaStats ecosystem and provides both parametric and non-parametric testing options.
Overview
Hypothesis tests for Julia
Use Cases
Best For
- Performing t-tests (one-sample, two-sample with equal or unequal variance) in Julia
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