Practice questions Week 4 1. Consider the first eigenvector: V1 = (-0.85,x,-0.16]'. What is the value of x so that tvi is an eigenvector? = 2. Using the eigenvector v, in the previous question, consider the second eigenvector v2 = [0.41, y, 0.37]'. What is the value of y so that vz is the second eigenvector? 3. Explain with your own words the objective of Principal Component Analysis. 4. What is the purpose of using regularization techniques in linear regression analysis? 5. When assessing a linear model to predict a particular dependent variable, what can you do to avoid look-ahead biases