Articles | Decision Science

Decision Science

A three-part series on Bayesian experimentation, sample efficiency, and optimal stopping.

• Part 1: Online Experiments with a Bayesian LensFrom conversion metrics to posterior intuition
• Part 2: How the Bayesian Approach Improves Sample EfficiencyPrior knowledge, adaptive designs, and why you need fewer participants
• Part 3: The Secretary Problem and Optimal StoppingWhen to stop looking and commit: the 37% rule and beyond
• Part 4: Multi-Armed Bandits and Thompson SamplingFrom fixed-horizon tests to adaptive allocation and regret minimization
• Part 5: Causal Inference from Observational DataPropensity scores, difference-in-differences, and what randomization buys you
• Part 6: Sequential Testing and Early StoppingMonitoring experiments in real time without inflating error rates