1. Stratified Sampling and Regression | Explanation of stratified sample selection, interpretation of a regression line for sleep vs. test scores, and limitations of linear regression in context. 2. Probability and Venn Diagrams | Solving for unknown probabilities using mutual exclusivity and independence in a Venn diagram with three overlapping events. 3. Binomial Distribution | Identification of discrete distribution type, calculating binomial probabilities for a spinner scenario, and computing cumulative probabilities. 4. Large Data Set and Rainfall | Importance of data cleaning, interpolation for upper quartile, calculation of standard deviation, and critique of midpoint assumptions in grouped data. 5. Hypothesis Testing | Identification of logical errors in hypothesis test setup, determining critical region and actual significance level for testing a proportion using the binomial distribution.