Regression and data analysis techniques for health research. Practical approaches to linear and logistic regression, multivariable modelling, interaction, variable selection, confounding, and measures of association. Computer-based laboratory exercises using statistical software applied to health datasets. Prerequisite: STAT 302 or STAT 305, with a minimum grade of C-. Recommended: HSCI 230.
Regression and data analysis techniques for health research. Practical approaches to linear and logistic regression, multivariable modelling, interaction, variable selection, confounding, and measures of association. Computer-based laboratory exercises using statistical software applied to health datasets. Prerequisite: STAT 302 or STAT 305, with a minimum grade of C-. Recommended: HSCI 230.
