What's Being Tested on the Exam (Based on Practice Final + Notes from Image) Probability & Conditional Probability Basic probability rules, complements, intersections, unions. Conditional probability (P(A|B), P(B|A)), Bayes' Theorem reasoning. Contingency tables with joint and marginal probabilities. Possible: Chi-squared test for independence (if contingency table is categorical data). No binomial distribution expected on this exam. Regression Problems Two total regression problems: One standard regression problem. One involving backward elimination for variable selection. One of these will involve dummy variables: Discrete (categorical) variable with 3 distinct categories. You'll need to create dummy variables for this case. Example: Loan defaulting probability with 3 categories from the practice test (scorecard usage case). Portfolio Problems Portfolio expected return (ER) and standard deviation (risk) with two different assets. Different portfolio weights will be given (e.g., heavy weighting on one asset vs. balanced). Must determine which portfolio is best in terms of risk-return trade-off. Descriptive Statistics for Assets Expected return, variance, standard deviation, covariance, correlation. May be a precursor step to the portfolio problem. Model Interpretation & Hypothesis Testing Interpret regression coefficients (continuous and dummy). Assess model fit (R, adjusted R). Hypothesis testing for coefficients (t-tests) and full model significance (F-test). Prediction intervals for given