2014/2015, Semester 2

Yale-NUS College (Yale-NUS College)

Modular Credits: 5

Chapter 1 is on probability, or data generating processes. This occupies the first four weeks of the course, and covers, among other topics, the axioms of probability, random variables, moments and functions of random variables, distribution families and limiting distributions.

Chapter 2 introduces classical or frequentist inference, covering likelihood functions, maximum likelihood estimation, frequentist properties of estimators, and classical measures of uncertainty. It occupies weeks 5 to 7.

Chapter 3 introduces Bayesian inference, including priors, posteriors, methods for computing posteriors and Bayesian decision theory. It occupies weeks 8 to 10.

Chapter 4, during weeks 11 to 13, covers hypothesis testing, from the basic principles to different kinds of tests, including Wald, likelihood ratio and permutation tests.

- Mid-term test 1 (0.15)
- Mid-term test 2 (0.15)
- Mid-term test 3 (0.15)
- Project (0.2)
- Final exam (0.35)