Step 1: Standardize the input variables to remove centering and scaling issues MinorityPop FireReport CrimeRate HouseAge Income Declination 0. 60813 2 . 4141 1. 6597 -0. 26471 -0. 71948 0.3 -0. 93769 -0. 085484 1.9823 -0. 69415 2. 5894 0. 02 -0. 86843 -0. 52914 -0. 64479 0. 84755 -0. 001968 0. 02 -0. 9251 -0. 48585 -0. 045629 1. 3457 -0. 10436 0.4 -0. 41507 0 . 35817 -0.32217 1. 3328 -0. 36984 1.1 0. 26496 1. 8731 0 . 09264 1. 0279 -0. 77842 1.9 -1. 0573 -1. 0377 -0. 82915 -0. 79722 0. 65186 0 . 02 -1. 0605 -0. 65899 -0.96742 -1. 3254 1.2832 0. 02 Step 2: Find the Principal Components that reflects 90% of the variance The output of the eigenvector decomposition is shown below EIG VEC1 EIG VEC2 EIG VEC3 EIG VEC4 EIG VEC5 EIG VALUES 0. 36152 0. 4631 0. 6359 -0. 23164 -0. 44365 0. 30403 -0. 79771 -0. 032112 0. 20208 0. 2347 -0. 51644 0 . 32004 0 . 45163 -0.17507 -0. 09827 0. 78804 -0.36704 0. 76178 0 . 012363 0. 5031 -0. 73286 -0. 18233 -0. 42001 0. 89233 -0.16984 0. 70763 0. 089741 0 . 48684 0. 4747 2. 7218 Part A (6 points). Identify the number of required principal components that reflects 90% of the variance