BIOST 2049 - APPLIED REGRESSION ANALYSIS

Minimum Credits: 3
Maximum Credits: 3
This is an introductory course in statistical modelling intended for Masters or PhD students in biostatistics or other disciplines who have already had basic training in statistical methods. The course focuses on all types of regression methods with the following learning objectives: To fit and interpret linear regression models with multiple continuous and/or categorical predictors. To fit and interpret generalized linear models (GLMs) with emphasis on logistic and Poisson regression. To justify and apply standard modelling procedures using data, including model interpretation and assessment of model adequacy. To analyze data sets taken from the fields of medicine and public health. To develop oral and written communication skills through the description of analytic strategies and the summarization and interpretation of results.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SU3 Basis
Course Requirements: PREQ: BIOST 2039 or BIOST 2041

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