Principles of data analysis and advanced statistical modeling. Bayesian inference, prior and posterior distributions, multi-level models, model checking and selection, stochastic simulation by Markov Chain Monte Carlo. Prerequisite: Statistical Science 210 and (Statistical Science 230, 231, or 240L) and (Mathematics 202, 202D, 212, or 222) and (Computer Science 101L, Computer Science 102L, Computer Science 201, or Engineering 103L) and (Mathematics 216, 218, or 221). Corequisite: Statistical Science 211.
Prerequisites
Prerequisite: STA 210 and (STA 230, 231, or 240L) and (MATH 202, 202D, 212, 219, or 222) and (COMPSCI 101L, COMPSCI 102L, COMPSCI 201, or EGR 103L) and (MATH 216, 218, or 221). Pre or corequisite: STA 211.
Statistical Science