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A G M N o Q R s T U V w X Y B C D E H K L 04 The Credit Approval Decisions data below provide information on credit history for a sample of banking customers Use regression analysis to identify the best model for predicting the credit score as a function of the other numerical variables using both the p-value and t-statistic criteria How do the models compare? Which would you choose? Use a level of significance of 0.05. Credit Score 6 7 0.68 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 45 47 48 49 50 51 52 53 54 55 56 Vears of Credit Historytevolving Balance (sRevolving Utilization (%) 730 20 11420 0.23 578 9 7300 0.71 682 11 20100 0.52 630 15 12900 532 12 5800 0.77 800 22 9100 0.14 738 7 35300 0.22 6251 5 22900 0.64 596 17 16600 0.51 665 24 9300 0.34 705 19 22100 0.16 SOS 16 12600 0.84 570 6 7800 0.72 625 3 37500 0.88 779 13 6200 0.08 807 10 10600 0.04 645 7 17400 0.57 528 14 27100 0.78 816 20 13500 0.05 768 2 11300 0.72 560 4 2600 0.98 6221 9 8500 0.35 647 13 16100 0.23 6931 3 3 3400 0.11 654 12 7600 0.05 700 15 20400 0.24 706 9 11800 0.13 640 7 29200 0.85 512 2 2100 1 682 12 7700 0.07 490 5 1100 0.84 587 3 8600 0.63 2041 17 12900 0.28 708 22 10100 0.21 590 18 31100 0.79 625 8 16300 0.56 700 16 9800 0.12 779 13 6200 0.06 807 10 10600 0.05 645 7 17400 0.58 14 27100 0.77 806 20 13500 0.04 765 2 11300 0.72 572 4 2300 0.97 605 10 12150 0.84 707 11 11800 0.18 641 8 29200 0.83 514 3 2100 0.99 600 18 29100 0.77 7381 15 131001 0.25 541 A G M N o Q R s T U V w X Y B C D E H K L 04 The Credit Approval Decisions data below provide information on credit history for a sample of banking customers Use regression analysis to identify the best model for predicting the credit score as a function of the other numerical variables using both the p-value and t-statistic criteria How do the models compare? Which would you choose? Use a level of significance of 0.05. Credit Score 6 7 0.68 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 45 47 48 49 50 51 52 53 54 55 56 Vears of Credit Historytevolving Balance (sRevolving Utilization (%) 730 20 11420 0.23 578 9 7300 0.71 682 11 20100 0.52 630 15 12900 532 12 5800 0.77 800 22 9100 0.14 738 7 35300 0.22 6251 5 22900 0.64 596 17 16600 0.51 665 24 9300 0.34 705 19 22100 0.16 SOS 16 12600 0.84 570 6 7800 0.72 625 3 37500 0.88 779 13 6200 0.08 807 10 10600 0.04 645 7 17400 0.57 528 14 27100 0.78 816 20 13500 0.05 768 2 11300 0.72 560 4 2600 0.98 6221 9 8500 0.35 647 13 16100 0.23 6931 3 3 3400 0.11 654 12 7600 0.05 700 15 20400 0.24 706 9 11800 0.13 640 7 29200 0.85 512 2 2100 1 682 12 7700 0.07 490 5 1100 0.84 587 3 8600 0.63 2041 17 12900 0.28 708 22 10100 0.21 590 18 31100 0.79 625 8 16300 0.56 700 16 9800 0.12 779 13 6200 0.06 807 10 10600 0.05 645 7 17400 0.58 14 27100 0.77 806 20 13500 0.04 765 2 11300 0.72 572 4 2300 0.97 605 10 12150 0.84 707 11 11800 0.18 641 8 29200 0.83 514 3 2100 0.99 600 18 29100 0.77 7381 15 131001 0.25 541
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