Statistical hypothesis testing is used in e-commerce to help companies make the right decisions when analyzing data from A/B tests, ad-hoc analyses, and building models. A statistical test compares a null hypothesis (H0) to an alternative hypothesis (H1) using a sample of data. It estimates the probability of observing the sample if the null hypothesis is true. If this probability is low, the null hypothesis can be rejected in favor of the alternative. The key parameters of a statistical test are the significance level, which is the probability of falsely rejecting the null hypothesis, and power, which is the probability of correctly rejecting the null when the alternative is true. In e-commerce, increasing sample size or effect size can improve