Select one of the options below:
Covers applied regression methods, including: interaction; model assumptions and diagnostics, selection, and validation; penalized estimation; GLMs; mixed models; factorial ANOVA; ANCOVA. Also covers basic categorical data analysis and non-parametrics. Strong emphasis on application and interpretation; lesser emphasis on mathematics.
Assignments involve reproducing analyses in published scientific papers and open ended data analysis projects. Data analyses are performed using JMP software.
If you should have any questions about this course offering, please contact Graduate & Online Program Coordinator, Alex Peitsmeyer.
STAT 301 (Introduction to Statistical Methods) or STAT 315 (Intro to Theory and Practice of Statistics); Credit not allowed for both STAT 331 and STAT 380A1.