Essentials of Factor Analysis (Online)
Date:
01/07/2025
Organised by:
University of Hertfordshire
Presenter:
Prof Neil H. Spencer
Level:
Intermediate (some prior knowledge)
Contact:
Prof. Neil Spencer
statistics@herts.ac.uk
Venue: Online
Description:
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.
The free statistical software jamovi will be used in the course but SPSS can instead be used by course delegates, if preferred. Instructions on how to obtain and install jamovi will be given and you will need to have whichever software you want to use installed on your computer before the start of the course.
Prerequisites: a basic understanding of correlation and regression.
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.
Cost:
£129
Website and registration:
Region:
East of England
Keywords:
Quantitative Data Handling and Data Analysis, Principal components analysis, Factor analysis, ICT and Software, Quantitative Software, jamovi
Related publications and presentations from our eprints archive:
Quantitative Data Handling and Data Analysis
Principal components analysis
Factor analysis
ICT and Software
Quantitative Software