Validating Type I and II Errors in A/B Tests in R
In the below work, we will intentionally leave out statistics theory and attempt to develop an intuitive sense of what type I(false-positive) and type II(false-negative) errors represent when comparing metrics in A/B tests. One of the problems plaguing the analysis of A/B tests today is known as the “peeking... Read more

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