Principal components analysis offers researchers a "feel" for analysing particular sets of multidimensional data. A multivariate analysis technique applied to a wide variety of settings such as medicine and chemistry as w...

Buy Now From Amazon

Product Review

Principal components analysis offers researchers a "feel" for analysing particular sets of multidimensional data. A multivariate analysis technique applied to a wide variety of settings such as medicine and chemistry as well as the social sciences, principal components analysis can be used to determine the number of factors to be retained in a factor analysis; for extracting the initial factors in a factor analysis; and in selecting a subset of variables to represent a much larger set. It is particularly useful in coping with multicolinearity in regression analysis, a persistent problem in behavioral and social science data sets.



Similar Products

Basics of Multivariate Analysis II (Principal Component Analysis): Theory and Exercise using RFactor Analysis: Statistical Methods and Practical Issues (Quantitative Applications in the Social Sciences)Bayes' Theorem Examples: A Visual Introduction For BeginnersHypothesis Testing: A Visual Introduction To Statistical SignificanceIntroduction to Factor Analysis: What It Is and How To Do It (Quantitative Applications in the Social Sciences)A Gentle Introduction to StataMultilevel Modeling (Quantitative Applications in the Social Sciences)Understanding Regression Assumptions (Quantitative Applications in the Social Sciences)