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Principal Components and Exploratory Factor Analysis with SPSS

July 26 @ 9:00 am - 12:00 pm

This seminar will give a practical overview of both principal components analysis (PCA) and exploratory factor analysis (EFA) using SPSS. We will begin with variance partitioning and explain how it determines the use of a PCA or EFA model. For the PCA portion of the seminar, we will introduce topics such as eigenvalues and eigenvectors, communalities, sum of squared loadings, total variance explained, and choosing the number of components to extract. For the EFA portion, we will discuss factor extraction, estimation methods, factor rotation, and generating factor scores for subsequent analyses. The seminar will focus on how to run a PCA and EFA in SPSS and thoroughly interpret output, using the hypothetical SPSS Anxiety Questionnaire as a motivating example.  The notes for the workshop can be found here; you can sign up here.

NOTE:  All researchers are welcome to attend this workshop.  However, there will be NO online component.  Please sign up only if you can attend in person.

Details

Date:
July 26
Time:
9:00 am - 12:00 pm
UCLA OIT