Randomized experiments, a.k.a. AB tests, are the established standard in the industry to estimate causal effects. Randomly assigning the treatment (new product, feature, UI, …) to a subset of the population (users, patients, customers, …) we ensure that, on average, the difference in outcomes (revenue, visits, clicks, …) can be attributed to the treatment. Established companies like Booking.com report constantly running thousands of AB tests at the same time. And newer growing companies like Duolingo attribute a large chunk of their success to their culture of experimentation at scale.
Introduction to Bayesian Linear Regression
The Bayesian vs Frequentist debate is one of those academic arguments that I find more interesting to watch than engage in. Rather than enthusiastically jump in…