Final exam, integrated assessment
Learning objectives
- Test cumulative recall across the entire curriculum (Parts 0-10)
- Identify cross-topic gaps before applying the material to research
- Practice under randomised draw to prepare for industry-style or PhD-qualifier-style assessments
The final exam draws 20 questions at random from the full bank of approximately 867 MCQs spanning every part of the textbook. Rerun the quiz for a fresh draw any time, each session samples a different subset.
Topics span: probability foundations (Part 0), estimation theory (Part 1), hypothesis testing and replication (Part 2), confidence intervals and bootstrap (Part 3), linear regression done seriously (Part 4), generalised linear models (Part 5), causal inference (Part 6), Bayesian methods (Part 7), resampling and nonparametrics (Part 8), ML for researchers (Part 9), and integrated capstones (Part 10).
Suggested time: 30-45 minutes including rationale reading. Threshold for "ready to apply this material to real research": 80% (16 / 20). If you score below that, identify the weak per-part areas and review those before the next attempt.
Mark final exam complete →