Statistics 3: Advanced Statistics

0.5 credits · Undergraduate

Advanced statistical methods, especially in computational statistics: linear and generalized linear models; classification methods; variable selection; resampling; decision trees; neural networks; Markov Chain Monte Carlo methods; Bayesian estimation; multilevel and hierarchical models; and experimental design. Additional topics as time allows. Prerequisite: MATH 2560H or a minimum 75% in each of MATH 1051H and 1052H, or permission of instructor.