In this lecture, we review the basics of hypothesis testing (type-I error, type-II error, statistical power) and the fundamental processes underlying hypothesis testing that create relationships among these things. We then dig deeper into the assumptions necessary for using parametric tests, like the Student's t-test, and non-exact parametric tests, like the Chi-square test (e.g., what the "continuity assumption" is with regard to the Chi-square test and the related inference).