Exercise Solution 3.17

1. W has a singular covariance matrix because its components are linearly related.
2. V has a non-singular covariance matrix. Although its components are related, that relationship in not linear.
3. X has a non-singular covariance matrix because its components are not linearly related.
4. Y has a singular covariance matrix because its components are linearly related.