Handbook

Modern research often involves the analysis of data for more than one variable and in this regard, linear models are the most widely used class of models. Linear models relate a response variable to one or more explanatory variables enabling researchers to answer important research questions and make predictions about how variables will respond. These methods are used in many areas including biological science, economics, engineering, medical science and psychological science. Topics covered in this subject include simple and multiple linear regression, response and explanatory variable transformations, ANOVA and ANCOVA, as well as more modern methodologies such as generalized linear models and linear mixed effects models. This subject has a strong emphasis on preparing students for future careers in statistics.