Using SPSS to carry out Principal components analysis (2018)

This video provides an overview of Principal components analysis in SPSS as a data reduction technique (keep in mind the assumption is you are working with measured variables that are reasonably treated as continuous). I review basic options in SPSS, as well as discuss strategies for identifying the number of components to retain (including parallel analysis) and naming those factors. I discuss Varimax rotation and Promax rotation, as well as the generation of component scores. Finally, I illustrate how you can use component scores in subsequent analyses such as regression. This is a fairly long video, but it was aimed at being comprehensive! You can perform the same steps I illustrate by downloading the data here ( https://drive.google.com/open?id=1Ds7LXr-_NUP3FYCxcd0kxv9WHowUwGqc ) and following along.

You can go to the site referenced to carry out the parallel analysis here: https://analytics.gonzaga.edu/parallelengine/

The IBM website referencing the KMO measure of sampling adequacy is located here: http://www-01.ibm.com/support/docview.wss?uid=swg21479963

For more instructional videos and other materials on various statistics topics, be sure to my webpages at the links below:

Introductory statistics:
https://sites.google.com/view/statisticsfortherealworldagent/home
Multivariate statistics:
https://sites.google.com/view/statistics-for-the-real-world/home

Видео Using SPSS to carry out Principal components analysis (2018) канала Mike Crowson