2Test

2Test is an open-source statistical software library for two-sample hypothesis testing. It provides tools to compare two data samples to assess differences in means, variances, or distributions. The library offers a consistent interface across test types to facilitate reporting and reproducibility.

Supported tests include independent two-sample t-test and Welch's t-test for means; F-tests for variances; and nonparametric alternatives such as the Mann-Whitney U test and the Kolmogorov-Smirnov test for distributions. The package also computes effect sizes (for example, Cohen's d or rank-biserial correlation) and reports p-values and confidence intervals. It includes options for multiple testing corrections, such as Bonferroni and false discovery rate adjustments.

Data input supports formats such as CSV, JSON, and spreadsheet-like structures; outputs are designed for reporting and visualization. The library provides APIs for several programming environments to integrate into data analysis workflows.

Development and governance are community-driven and cross-platform, with contributions from researchers and practitioners in statistics, data science, and related fields. It is used in educational settings as well as practical research where controlled comparisons between two groups are required.

2Test is released under an open-source license and is accompanied by documentation, tutorials, and example datasets. The project maintains interoperability with other statistical tools and releases updates to add tests and improve performance.