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. Which silhoutte score creates the best paritioned clusters?

a. Average Cluster Silhoutte Score = -1

b. Average Cluster Silhoutte Score = 0

c. Average Cluster Silhoutte Score = .5

d. Average Cluster Silhoutte Score = 1

1. What is linkage in a hierachical clustering model? Provide a description of one type of linkage?

1. List five distance functions that can be used to measure similarity.

1. 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.

Degree of correlation between variables