Previous Chapter Chapter 35: Factor Analysis Next Chapter

  • Citations
  • Add to My List
  • Text Size

Factor Analysis
Factor analysis
Introduction

Factor analysis attempts to identify the underlying structure in a data set by defining a small number of factors that capture the variation in the collected data. Factor analysis assumes that relationships between variables are due to the effects of underlying factors and that observed correlations are the result of variables sharing common causes. Describing a data set in terms of factors (or latent variables as they are sometimes called) is often useful at a theoretical level as it may identify the underlying processes which determined the correlations among the variables. This often allows a simpler and clearer interpretation of the relationships in the data. Factor analysis is also useful at a more practical level as it reduces the number of variables ...

Looks like you do not have access to this content.

Login

Don’t know how to login?

Click here for free trial login.

Back to Top

Copy and paste the following HTML into your website