This document discusses hypothesis testing, which is a method in inferential statistics used to make judgments about the probability of observed differences between groups occurring by chance. There are two main steps in hypothesis testing: establishing a null hypothesis (H0) and an alternative hypothesis (Ha or H1), and selecting a suitable test of significance or test statistic based on factors like the number and independence of samples. The test statistic is then compared to a critical or rejection region determined beforehand to either accept or reject the null hypothesis. Types of errors that can occur in hypothesis testing are also discussed.