0.1.0 - 2026-06-30

  • Added descriptive statistics for one-dimensional finite samples.
  • Added Normal and Student's t distribution helpers.
  • Added one-sample, paired, Welch, and pooled t-tests.
  • Added average-rank utilities.
  • Added asymptotic, exact, and auto Mann-Whitney U tests.
  • Added JSONL fixtures generated from pinned NumPy, SciPy, and Statsmodels references.
  • Added upstream-derived fixture coverage notes.
  • Added nan_policy: :raise | :propagate | :omit for current public statistics APIs.

  • Added t-test confidence intervals and optional Cohen's d / Hedges' g effect sizes.
  • Added Mann-Whitney common-language and rank-biserial effect sizes.
  • Added effect_size.cliffs_delta as an alias of Mann-Whitney rank-biserial.
  • Added dataframe-style columns: and pairs: wrappers for t-tests and Mann-Whitney U tests, including optional Explorer.DataFrame support when Explorer is loaded by the caller.
  • Added opt-in tensor extraction for dataframe columns with input: :tensor and opt-in Nx reduction paths with backend: :tensor.
  • Added the Statwise.Visualization API for semantic chart construction, Vega-Lite export, optional Livebook/Kino display, themes, faceting, and composition.
  • Added statistical result annotations for categorical plots, including t-test and Mann-Whitney comparison brackets, computed per-facet tests, and p-value/statistic/effect-size labels.
  • Added runnable Livebook galleries for visualization features and statistical test selection, variants, dataframe-style inputs, and plot annotations.
  • Added a Python-reference benchmark harness for comparing Statwise against pinned NumPy, SciPy, and Statsmodels calls.
  • Added benchmark JSON output and baseline comparison support for regression checks.