Statistics

Knows mean, median, variance, what a p-value roughly means, and why sample size matters.

Runs t-tests, chi-squared tests, understands Type I/II errors, computes confidence intervals.

Designs A/B tests, corrects for multiple comparisons, uses bootstrap, cross-validation, and regression.

Applies Bayesian A/B testing, causal inference (diff-in-diff, IV), survival analysis, power analysis at scale.

Develops new statistical methods or contributes to causal ML research.