statistical-analysis

# Statistical Analysis ## Overview Conduct hypothesis tests (t-tests, ANOVA, chi-square), regression, correlation, and Bayesian analyses with systematic assumption checking, effect sizes, and APA-style reporting. The goal is an analysis a reviewer could not tear apart: the right test, verified assumptions, honest effect sizes, and a complete write-up. ## When to Use This Skill Use this skill when: - Conducting statistical hypothesis tests (t-tests, ANOVA, chi-square, non-parametric) - Performing regression or correlation analyses - Running Bayesian statistical analyses - Checking statistical assumptions and diagnostics - Calculating effect sizes and conducting power analyses - Reporting statistical results in APA format - Analyzing experimental or observational data for research --- ## Installation Use **uv** to install the libraries used in this skill. Pin versions in production; unpinned installs are fine for exploration. ```bash # Core frequentist stack (Python 3.10+; 3.12+ recommended for latest SciPy/ArviZ) uv pip install "pingouin>=0.6" "scipy>=1.11" "statsmodels>=0.14.6" pandas matplotlib seaborn # Bayesian modeling (PyMC 5 + ArviZ) uv pip install "pymc>=5.0" "arviz>=1.0" ``` **Compatibility notes (verified against pingouin 0.6.1, statsmodels 0.14.6, arviz 1.2, 2026):** - **Pingouin 0.6.0** renamed output columns to remove special characters: `p_val`, `cohen_d`, `CI95`, `p_unc` (previously `p-val`, `cohen-d`, `CI95%`, `p-unc` in 0.5.x). Examples below use th...