MATH 411 Scientific Data Analysis II 3.0 Credits
Scientific data analysis and experimental design. Topics include multiple regression and model selection, nonlinear and logistic regression, analysis of covariance, multi-factor analysis of variance, nested, factorial and repeated measures experimental designs, random effects, and introduction to bootstrap methods and randomization tests. Programming statistical applications in R will be included.
Repeat Status: Not repeatable for credit
Prerequisites: MATH 410 [Min Grade: C-]