This course is aimed at those with a working knowledge of basic statistical techniques and introduces methods for building analytical and predictive models involving multiple grouping factors, covariates and confounding variables. The General Linear Modelling (GLM) framework allows a wide range of models to be fitted, including multiple regression, factorial ANOVA, analysis of covariance, and models involving interactions. Models for binary, categorical and ordinal outcome variables are also discussed.

For simplicity, the course makes use of the jamovi software for demonstration and exercises. However, if preferred, any other advanced statistical software can be used (e.g. SPSS or R).

See our full range of courses (and options for bespoke courses) at https://go.herts.ac.uk/sscu or contact the course organiser, Professor Neil Spencer, at statistics@herts.ac.uk.

It is assumed that delegates have attended either the “Survey Design & Analysis” stream of courses (see here and here) or “Quantitative Data Analysis” stream of courses (see here and here) or already have a good knowledge of multiple regression and analysis of variance (ANOVA).

There is no formal assessment as part of this course.