Sample moments, the Central Limit Theorem (CLT), and hypothesis testing (z-tests and t-tests).
Recent additions include Machine Learning (ML) methods such as neural networks, decision trees, and regularization (LASSO/Ridge). 2. Strategic Focus for Page 1 & Chapter 1 Page 1 FRM PART I BOOK 2: QUANTITATIVE ANALysis...
Distinguishing between independent events (where the occurrence of one doesn't change the probability of the other) and mutually exclusive events (which cannot occur at the same time). Sample moments, the Central Limit Theorem (CLT), and
A "hot topic" for examiners, used to update prior probabilities as new information becomes available. the Central Limit Theorem (CLT)
Fundamentals of probability, random variables (discrete and continuous), and common univariate/multivariate distributions.