Building, evaluating, and interpreting GLMs in R for common actuarial applications.
These are the key learning objectives for Generalized Linear Models on SOA Exam PA. Paraphrased from the public SOA syllabus — we recommend also checking the current syllabus on soa.org before your exam sitting.
Fit GLMs with appropriate distributions and link functions
Evaluate model fit using deviance, AIC, and residual diagnostics
Interpret coefficients and generate predictions on new data
Upload your ACTEX Exam PA digital edition, scanned ASM pages, TIA handouts, or your own notes. exclam.ai extracts the Generalized Linear Models sections and generates flashcards automatically.
Generate multiple-choice quizzes specifically on Generalized Linear Models. Weak questions get re-surfaced until you get them right consistently.
Because Generalized Linear Models is 30–40% of your exam, losing it during review costs you. FSRS brings it back at the optimal moment.
SOA Exam PA has 4 topic areas. Generalized Linear Models is weighted at approximately 30–40% of the exam — here is where it sits relative to the other topics.
| Topic area | Weight |
|---|---|
| Problem Framing and Data Preparation | 15–25% |
| → Generalized Linear Models | 30–40% |
| Decision Trees and Ensemble Methods | 20–30% |
| Model Validation and Business Communication | 15–25% |
Translating a business problem into a predictive modeling question, exploratory data analysis, and feature engineering.
Fitting and tuning decision trees, random forests, and gradient boosting models in R.
Cross-validation, test set performance, sensitivity analysis, and communicating results to non-technical stakeholders.
Upload your ACTEX Exam PA digital edition, scanned ASM pages, TIA handouts, or your own notes. exclam.ai generates a fully guided study plan with adaptive flashcards and quizzes for this topic.