Trustworthy Online Controlled Experiments

Written by experimentation leaders from Microsoft, Google and Airbnb, this is the reference on A/B testing done properly. Covers metrics and the overall evaluation criterion, statistical power and sample sizing, the twyman's law effects that show a result is too good to be true, and the institutional memory that comes from running thousands of experiments. Deep on the traps of ratio metrics, sample ratio mismatch and interference between users.