1. Which statement about PCA is false?

a. Dimensions found by PCA are a linear combination of the original predictor variables.

b. Principle component vectors remove correlation among the original predictor variables .

c. Standardizing the original predictor variables does not affect the principle component vectors.

d. Each principle component vector explains a proportion of variance in the original predictor variables.

1.2 The effect of magniture differences among variables in a clustering model can be avoided by measuring similarity as

a. Distance between points in space.

b. Z score.

c. Records with the same number of variables.

d. Degree of correlation between variables.