Laurie knows that the unique and error variances are a relatively small portion of the total variance and wants to reduce the original set of variables into a smaller set of composite variables. Which type of multivariate analysis technique would be most appropriate for Laurie to use?
A) common factor analysis
B) k-means cluster analysis
C) principle components factor analysis
D) regression analysis
E) ANOVA

Question

Quizplus · Accepted Answer

Principle components factor analysis is designed to reduce a large number of variables into a smaller set of composite variables. It does this by identifying and combining variables that share common variance (i.e., extracting the principle components), which can then be used as new variables for subsequent analysis. Common factor analysis is similar, but assumes that the observed variables are a combination of common factors and unique factors. K-means cluster analysis is used for grouping cases into distinct groups based on their similarity. Regression analysis is used to examine the relationship between one dependent variable and one or more independent variables. ANOVA is used to compare means across two or more groups.

Laurie Knows That the Unique and Error Variances Are a Relatively