This is the follow on course to STA 570 and is intended for graduate students in quantitative sciences that will consistantly need statistics in their career.
Emphasis is placed on understanding the assumptions and concepts behind standard statistical tests and being able to correctly interpret computer results.
All classroom analysis is carried out using R, a free open-source data analysis language that is used by researchers and analysts around the world.
Topics covered include: matrix theory, general linear models, ANCOVA, contrasts, model selection, model diagnostics, experimental design, random effects, and generalized linear models.