Statistical Analysis

This is a comprehensive toolkit for running statistical tests in academic research contexts. It covers the standard workflow from test selection through assumption checking to APA-formatted reporting. The assumption checking module is especially practical, automatically running Shapiro-Wilk tests, Q-Q plots, and Levene's test before you commit to a test choice. It uses pingouin and statsmodels for the heavy lifting, which means you get effect sizes and diagnostics without manually calculating them. The decision tree and test selection guide are helpful if you're rusty on whether you need a Mann-Whitney U or Welch's t-test. Bayesian alternatives are included throughout, though the examples lean heavily on frequentist approaches. Best for researchers who want guardrails around proper statistical practice rather than just running tests blindly.