1. Data Presentation and Measures | Estimating mean and standard deviation from grouped data, interpreting histogram shape, effect of consistent overestimation on spread.

2. Correlation and Scatter Diagrams | Identification of correlation type, use of scatter plots for contextual analysis, assessing relationship strength and extrapolation limitations.

3. Set Theory and Probability | Venn diagram completion, calculation of conditional probabilities, determining independence using probability definitions.

4. Hypothesis Testing (Binomial) | Conducting two-tailed binomial tests, defining hypotheses, calculating critical values, interpreting outcomes in context.

5. Discrete Probability Distributions | Construction of probability tables for non-uniform distributions, calculating individual and cumulative probabilities.

6. Binomial Model and Estimation | Application of binomial probability to real-world contexts, probability estimation with given success rates, and evaluation of model suitability.