Tag: Bayesian
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P-value is the probability that the treatment effect is larger than zero (under certain conditions)
a.k.a. why you should (not ?) use uninformative priors in Bayesian A/B testing.
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Estimating long-term detection, win, and error rates in A/B testing
How to estimate the probability of detecting (a positive) treatment over a series of experiments? I use an (admittedly weird) fusion of frequentist concepts and Bayesian tooling to get to an answer.
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Estimating home court advantage in Lithuanian Basketball League with Gaussian Processes
I was looking for an excuse to play around with Gaussian Processes in a Bayesian Inference setting, and decided to revisit an older project about basketball in Lithuania. Just in time for this year’s finals!
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Modeling tenure effects the Bayesian way
After learning new things in Statistical Rethinking class, I took on to play around with an age-period-cohort-like model for disentangling tenure effects from seasonality & other factors. The Bayesian way.
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Getting to decisions faster in A/B tests – part 1: literature review
I set out on a journey to learn what statistical approaches the industry uses to get to faster decisions in A/B testing. This is the first post in the series in which I set the scene and summarize outcomes of my “literature review”.