Statistics Fundamentals

This gives Claude the statistical toolkit for quantitative finance work: descriptive stats, covariance matrices, OLS regression, hypothesis testing, and bootstrap resampling. You'll reach for it when analyzing return distributions, estimating correlations between assets, running CAPM regressions to get alpha and beta, or figuring out why your optimizer is producing unstable weights. It includes Ledoit-Wolf shrinkage for fixing ill-conditioned covariance matrices, which is the usual culprit when you have more assets than observations. The formulas cover the basics like volatility and skewness, plus practical diagnostics like R-squared and t-statistics. Also handles fat tails and non-normality, which matters because financial returns almost never pass a Jarque-Bera test.