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Factor analysis

Written by Ronny Gunnarsson and first published on September 25, 2015.
Last revised on September 8, 2019.

You must cite this article if you use its information in other circumstances. An example of citing this article is:
Ronny Gunnarsson. Factor analysis [in Science Network TV]. Available at: https://science-network.tv/factor-analysis/. Accessed April 15, 2025.
Suggested pre-reading What this web page adds
  1. Introduction to statistics
  2. Observations and variables
  3. Inferential statistics
  4. Choosing statistical analysis
  5. Associations and predictions
  6. Regression and correlation
 This web-page provides an introduction to factor analysis. Reading this will give you a brief understanding of this concept.

(This page is still under construction. Sorry for the inconvenience.)

Exploratory factor analysis (EFA) tries to identify factors not directly observed that may explain variation in several underlying directly measured observations / items. EFA may use techniques such as principal component analysis (PCA). Confirmatory factor analysis (CFA) tries to confirm that a hypothesized factor is correlated to underlying observations / items. CFA may use techniques such as structural equation modeling.

Introduction to Structural Equation Modelling by Nick Shryane.

Useful links

References

(This section is still under construction. Sorry for the inconvenience.)

You must cite this article if you use its information in other circumstances. An example of citing this article is:
Ronny Gunnarsson. Factor analysis [in Science Network TV]. Available at: https://science-network.tv/factor-analysis/. Accessed April 15, 2025.

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