Hypothesis Testing and Inference Questions

Fundamental framework and application of hypothesis testing and statistical inference. Topics include formulating null and alternative hypotheses, understanding Type I and Type II errors, interpreting p values and confidence intervals, selecting and applying common tests such as t tests, chi square tests, analysis of variance, and non parametric alternatives, checking test assumptions, and discussing statistical versus practical significance. Candidates should explain power, significance levels, effect sizes, and common pitfalls such as misinterpreting p values or violating independence assumptions. At more advanced levels, discuss limitations of null hypothesis significance testing, alternatives such as Bayesian inference, and guidance for when different approaches are appropriate.