This course covers advanced biostatistical methods with a focus on applications in kinesiology and health research. Students will explore a range of real-world problems that motivate the introduction of commonly used biostatistical methods. The course covers Exploratory Data Analysis, including data visualization techniques, handling missing data, and reporting summary statistics. It also includes Generalized Linear Models, focusing on methods for analyzing continuous, categorical, and count outcomes. Survival Analysis is discussed, with emphasis on methods for analyzing time-to-event outcomes. Additionally, the course addresses Longitudinal Data Analysis, which involves methods for analyzing repeated measurements over time.
This course is designed for students interested in learning advanced biostatistical methods and gaining hands-on experience by applying them to real-world data. The focus is on practical application rather than in-depth theoretical or mathematical foundations. Previous programming experience for data analysis using R, SAS, or other similar software is preferred but not necessary. Lecture examples will be given using the R language.