The PCA Debate

Recently a posting on the Research Methods Linked-In group asked what is Principal Components Analysis (PCA) in laymen terms and what is it useful for. The answers clearly reflected the two “camps”: social science researchers and data miners. For data miners PCA is a popular and useful data reduction method for reducing the dimension of dataset with many variables. For social scientists PCA is a type of factor analysis without a rotation step. The last sentence might sound cryptic to a non-social-scientist, so a brief explanation is in place: The goal of rotation is to simplify and clarify the interpretation … Continue reading The PCA Debate