Statistics Math

This is your foundational math toolkit for data science work. You get descriptive statistics, hypothesis testing (t-tests, chi-square, A/B tests), probability distributions, and linear algebra operations through NumPy, SciPy, and statsmodels. The code examples are practical: calculating p-values, checking for statistical significance, running regression with regularization, and computing effect sizes beyond just p-values. It covers 120 estimated hours to master and unlocks machine learning and deep learning skills. The best practice warnings are honest about common pitfalls like p-hacking and confusing correlation with causation. If you're moving from basic Python into actual data analysis, this bridges that gap with the statistical reasoning you need before jumping into ML frameworks.

Install to Claude Code

npx -y skills add pluginagentmarketplace/custom-plugin-data-engineer --skill statistics-math --agent claude-code