Tutorials in Quantitative Methods for Psychology· 2013
A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis
- 3,260citations
- 2013year
Short summary
This tutorial introduces Exploratory Factor Analysis (EFA), a statistical technique for identifying underlying structures in data, and provides practical guidance for its application.
AI-generated from the title and abstract; the full text is not read.
Key points
- Explains the core statistical technique of Exploratory Factor Analysis (EFA).
- Outlines EFA's main assumptions and criteria for use.
- Provides a practical guide with an SPSS example for running EFA.
- Offers instructions on how to interpret EFA output and write up results.
AI-generated from the title and abstract; the full text is not read.
Abstract
The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.
The authors' abstract, as published at the source. Tutorials in Quantitative Methods for Psychology, 2013 · DOI ↗
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Field: Computer Networks and Communications
Computer Networks and CommunicationsComputer Science