Data Analysis 8. The primary goal of principal component analysis is to A. Divid

Question

Data Analysis 8. The primary goal of principal component analysis is to A. Divide a set of multivariate observations into classes. B. Assign a particular multivariate observation to one of several classes C. Characterize the correlation structure between two sets of variables by replacing them by two 1 smaller sets of variables which are highly correlated. variables of interest variables that explains a large portion of the total variability D. Find the variables among a set of predictor variables that are the best predictors of a set of E. Explain the variability in a large set of variables by replacing it by a smaller set of transformed

Explanation / Answer

Principal component analysis uses orthogonal transformation

to transform a set of correlated variables into a set of linearly

uncorrelated variables, which are called principal components.

The number of principal components are less than or at most

equal to the number of variables. The first principal

component has the highest possible variance, and the next

component will have highest possible variance under the

constraint that it is orthogonal to the first one and so on.

So here, Option (E) is the correct explanation of the goal of

principal component analysis. (Ans).

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