Superiority vs Non-Inferiority Trials in AB Testing
Not every experiment needs to show improvement — sometimes proving you haven’t made things worse is enough. A practical guide to non-inferiority trial design.
Ab-Testing
Bayesian A/B Test is NOT immune to peeking
Practical guide: PyMC examples, hierarchical models, loss functions, HDI, and safe stopping rules
Linearization: Turning Ratio Metrics into Per-User Metrics
A simple algebraic transformation that converts ratio metrics into independent per-user values, making T-tests and sensitivity techniques directly applicable
Delta Method for Ratio Metrics in AB Testing
Correct variance estimation for ratio metrics using the Delta Method — and why naive approaches quietly break your confidence intervals
CUPED: Reducing Metric Variance with Pre-Experiment Data
How CUPED uses pre-experiment covariates to cut metric variance and boost AB test sensitivity — with a rigorous proof of what works and what silently breaks