Dr Ben Stewart-Koster
Regression is at the foundation of many advanced statistical modelling methods, so it is important to gain a firm foundation in regression with multiple predictor variables.
This workshop follows the perspective of modern statistical emphasis on modelling, rather than null hypothesis testing and builds on the Introduction to regression workshop, introducing additional variables. This emphasises the strong links between the testing of a research hypothesis and the model, where multiple processes may be affecting the response variable of interest. Using a worked example, we will step you through the process of specifying a multiple linear regression model and guide the interpretation of the outputs. In particular we will look at how to evaluate the fit using summary statistics as well as diagnostics when comparing several models. The focus will be on understanding the inputs and interpreting the outputs. Participants will gain an understanding of how to use multiple variables in regression that will help equip them to build their own models in future.