This half-day course covers the essentials of factor analysis - a technique that can be used to explore a dataset and obtain an understanding of the true unobserved factors underlying the observed responses for the variables that have been measured. It can also be used for feature extraction in data science applications.

It is ideal for those working in the social sciences and business who wish to obtain a better understanding of their data, and those working in machine learning who are looking to extract features from their data.

The course will include issues of deciding on the number of factors to be extracted, checking assumptions and sample sizes, choosing extraction methods, rotating factors, interpreting and giving names to factors, and factor scores. Microsoft Excel will be used to demonstrate the methods, using a free add-in designed (by the author of this course) to undertake multivariate analyses.

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.

A basic understanding of correlation and regression.