STATS 510
Probability and Distribution Theory
Essential concepts of probability and distribution theory that are important for statistical inference including: random variables, probability, conditional probability, distribution functions, independence, modeling dependence, transformations, quantiles, order statistics, laws of large numbers, central limit theorem, and sampling distributions.
Prerequisites & course information
Graduate standing or ([MATH 205 or 215 or 285] and [MATH 296 or 297 or 351 or 451)]. (Prerequisites enforced at registration.) (3). May be repeated for a maximum of 6 credits.
Sources
- Course catalogue ↗2026-2027