Academic Calendar - 2024
Western University Academic Calendar. - 2024
Biostatistics
Epidemiologists work with categorical data (e.g. healthy, sick, dead) and with time to event data (e.g. time to death). This course introduces analytic methods of such data, expanding on aspects of study design and analysis introduced in Epidemiology 2200A/B. It requires a prior introduction to analyses of continuous data.
Prerequisite(s): Biology 2244A/B or Statistical Sciences 2244A/B, and Epidemiology 2200A/B, with a minimum mark of 75% in each.
Extra Information: 2 lecture hours and 1 laboratory hour.
Course Weight: 0.50
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This course covers frequently used multivariable regression models (linear for continuous outcomes and logistic for binary outcomes) in health research. By the end of the course students will (i) understand and critique applications of regression models appearing in the biomedical literature and (ii) carry out their own analyses.
Prerequisite(s): Biostatistics 3100A and Epidemiology 3200A, with a minimum mark of 70% in each.
Extra Information: 2 lecture hours and 1 laboratory hour.
Course Weight: 0.50
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This course introduces students to the use of both commercial software (i.e., SAS and Stata) and open-source software (R via RStudio) for data management, exploratory data analysis, data generation, and inferential statistical analysis. Examples will be used throughout the course to illustrate the advantages and disadvantages of each software.
Prerequisite(s): Biology 2244A/B or Statistical Sciences 2244A/B, and Epidemiology 2200A/B with marks of at least 75% in each; and registration in a module in Epidemiology and Biostatistics.
Extra Information: 2 lecture hours, 1 laboratory hour.
Course Weight: 0.50
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Biostatistics
Epidemiologists work with categorical data (e.g. healthy, sick, dead) and with time to event data (e.g. time to death). This course introduces analytic methods of such data, expanding on aspects of study design and analysis introduced in Epidemiology 2200A/B. It requires a prior introduction to analyses of continuous data.
Prerequisite(s): Biology 2244A/B or Statistical Sciences 2244A/B, and Epidemiology 2200A/B, with a minimum mark of 75% in each.
Extra Information: 2 lecture hours and 1 laboratory hour.
Course Weight: 0.50
Return to top
This course covers frequently used multivariable regression models (linear for continuous outcomes and logistic for binary outcomes) in health research. By the end of the course students will (i) understand and critique applications of regression models appearing in the biomedical literature and (ii) carry out their own analyses.
Prerequisite(s): Biostatistics 3100A and Epidemiology 3200A, with a minimum mark of 70% in each.
Extra Information: 2 lecture hours and 1 laboratory hour.
Course Weight: 0.50
Return to top
This course introduces students to the use of both commercial software (i.e., SAS and Stata) and open-source software (R via RStudio) for data management, exploratory data analysis, data generation, and inferential statistical analysis. Examples will be used throughout the course to illustrate the advantages and disadvantages of each software.
Prerequisite(s): Biology 2244A/B or Statistical Sciences 2244A/B, and Epidemiology 2200A/B with marks of at least 75% in each; and registration in a module in Epidemiology and Biostatistics.
Extra Information: 2 lecture hours, 1 laboratory hour.