A data scientist wants to reduce the dimensionality of a dataset with 50 numeric variables before clustering. In SAS, which procedure is most commonly used to perform Principal Component Analysis?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — d is correct because SAS provides two procedures for PCA: PROC PRINCOMP, which is specifically designed for principal component analysis, and PROC FACTOR with METHOD=PRINCIPAL, which computes principal components as part of factor analysis. Both are valid and commonly used.
Full explanation below image
Full Explanation
D is correct because SAS provides two procedures for PCA: PROC PRINCOMP, which is specifically designed for principal component analysis, and PROC FACTOR with METHOD=PRINCIPAL, which computes principal components as part of factor analysis. Both are valid and commonly used. A is wrong because PROC PCA does not exist as a standalone procedure in SAS. B alone or C alone would be partially correct, but D captures both valid options.