ABSTRACT
This chapter explains the complex nature of large and mid-sized datasets and how to reduce the number of variables without losing much information using principal component analysis and common factor analysis. It addresses the concern of multicollinearity due to related independent variables. The chapter includes sections on the purpose and history of factor analysis in planning. The mechanics section contains definitions of key terms, requirements, the mathematics that undergirds the factor analysis process, and how to interpret results. The “Step by Step” section explains how to run a factor analysis in SPSS and R. This chapter concludes with real-life examples of factor analysis in planning.
