This video demonstrates the use of SPSS for carrying out Principal components analysis (PCA). I cover the topics of component retention (using Kaiser criterion, scree plot, parallel analysis) and interpretation (via orthogonal and oblique rotation). I also demonstrate how to obtain component scores.
A copy of the dataset can be downloaded here:
https://drive.google.com/file/d/1ItnkZ68hBWYtKDHZJ29eLGYs7TgqH2FU/view
A copy of the Powerpoint can be downloaded here:
https://drive.google.com/file/d/16-arUCU95wrU2G-aAykmiVbMWAzFEsJF/view
Link to Parallel analysis engine:
https://analytics.gonzaga.edu/parallelengine/
Here is the link to the PCA example at the UCLA Institute for Digital Research and Education: https://stats.idre.ucla.edu/spss/output/principal_components/
More videos and resources on multivariate statistical procedures can be found here: https://sites.google.com/view/statistics-for-the-real-world/home