Covers linear models, generalized linear and non-linear regression, and models. Includes interpretation of parameters, including collapsibility and non-collapsibility, estimating equations; likelihood; sandwich estimations; the bootstrap; Bayesian inference: prior specification, hypothesis testing, and computation; comparison of approaches; and diagnostics. Prerequisites: either STAT 512 and STAT 513, or BIOST 522 and BIOST 523; and either STAT 502 and STAT 504/CS&SS 504, or BIOST 514 and BIOST 515. Recommended Preparation: matrix algebra from a course at the level of BIOST 533/STAT 533. Offered: jointly with STAT 570; Autumn