The Peeking Problem
[ Live ]Checking your A/B test results early feels harmless. A live simulation of what it actually costs you, in both frequentist and Bayesian terms.
- [ Statistics ]
- [ TypeScript ]
- [ Data Viz ]
[ Coming soon ]
This page will hold personal projects I'm building on my own time, including a generalized experimentation library and some notes as I explore various causal inference use cases. Real write-ups are on the way.
Checking your A/B test results early feels harmless. A live simulation of what it actually costs you, in both frequentist and Bayesian terms.
How much should you trust surfboard volume calculators? A comparison of how thirteen recommendation systems disagree for the same surfer.
An open-source library for designing, analyzing, and reporting on A/B tests: the parts of an experimentation platform worth sharing publicly.
Notes and worked examples as I learn causal methods (diff-in-diff, synthetic control, instrumental variables) for questions where a randomized test isn't possible.