This course is designed for Biology graduate students with a basic introductory statistics/experimental design course and a working knowledge of R, a Language and Environment for Statistical Computing. In-depth exploration of all aspects of fitting linear models to continuous and categorical data, using mainly the lm function in R. Topics include residual analysis, maximum-likelihood methods, graphical presentations, ordinary least squares, model II regression, transformations, model selection with focus on information-theoretic approaches and outlier detection.
