MATH 582, Linear Statistical Models with Applications, 3 cr, 3 cl hrs

Prerequisite: MATH 483 or consent of instructor

An in-depth study of regression and analysis of variance models. Topics include multiple regressions and model
building, analysis of residuals, analysis of variance as regression analysis, generalized linear models, generalized
linear mixed models, nonlinear models, multifactor models with equal and unequal sample sizes, random and
fixed effects models, randomized complete block designs, and analysis of covariance.

also taught as MATH 489 (may be used as a Math Elective)