The accompanying Credit Approval Decisions data 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. E Click the icon to view the Credit Approval Decisions data - X Credit approval decisions data table What is the best model using the p-value criteria? Select the best answer below and fill in the answer boxes to complete your choice. (Type integers or decimals rounded to three decimal places as needed.) Credit Score Years of Credit Revolving Revolving History Balance (S) e (š) Utilization (%) OA. Credit Score = OYears + (OBalance B. Credit Score = 760.800 • (- 219.013) Utilization 728 21 11,420 0.23 576 8 7,300 0.71 680 13 20,100 0.52 Oc. Credit Score = +(OBalance 628 17 12,900 0.68 530 10 5,800 0.77 OD. Credit Score +OYears OE. Credit Score = OYears + (OBalance + (DUsilization OF. Credit Score = +OBalance + (OUtlization OG. Credit Score = +OYears + (Usization 798 21 9,100 0.14 736 6 35,300 0.22 623 6 22,900 0.64 594 18 16,600 0.51 663 22 9,300 0.34 703 18 22,100 0.16 What is the best model using the t-statistic criteria? Select the best answer below and fill in the answer boxes to complete your choice. 503 15 12,600 0.84 568 7 7,800 0.72 (Type integers or decimals rounded to three decimal places as needed.) 623 4 37,500 0.88 OA. Credit Score =+DYears + (DBalance 777 12 6,200 0.08 805 11 10,600 0.04 O B. Credit Score =+OBalance 643 17,400 0.57 Oc. Credit Score =+OBalance + ( Utlization 526 13 27,100 0.78 814 22 13,500 0.05 OD. Credit Score + DUiliation 766 4 11,300 0.72 OE. Credit Score +OYears + DUlization OF. Credit Score =•OYears + (Balance • DUtilization 558 4 2,600 0.98 620 8 8,500 0.35 645 14 16, 100 0.23 691 3,400 0.11 OG. Credit Score DYears 652 13 7,600 0.05 698 17 20,400 0.24 704 11,800 0.13 638 6. 29,200 0.85 510 3 2,100 1.00
The accompanying Credit Approval Decisions data 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. E Click the icon to view the Credit Approval Decisions data - X Credit approval decisions data table What is the best model using the p-value criteria? Select the best answer below and fill in the answer boxes to complete your choice. (Type integers or decimals rounded to three decimal places as needed.) Credit Score Years of Credit Revolving Revolving History Balance (S) e (š) Utilization (%) OA. Credit Score = OYears + (OBalance B. Credit Score = 760.800 • (- 219.013) Utilization 728 21 11,420 0.23 576 8 7,300 0.71 680 13 20,100 0.52 Oc. Credit Score = +(OBalance 628 17 12,900 0.68 530 10 5,800 0.77 OD. Credit Score +OYears OE. Credit Score = OYears + (OBalance + (DUsilization OF. Credit Score = +OBalance + (OUtlization OG. Credit Score = +OYears + (Usization 798 21 9,100 0.14 736 6 35,300 0.22 623 6 22,900 0.64 594 18 16,600 0.51 663 22 9,300 0.34 703 18 22,100 0.16 What is the best model using the t-statistic criteria? Select the best answer below and fill in the answer boxes to complete your choice. 503 15 12,600 0.84 568 7 7,800 0.72 (Type integers or decimals rounded to three decimal places as needed.) 623 4 37,500 0.88 OA. Credit Score =+DYears + (DBalance 777 12 6,200 0.08 805 11 10,600 0.04 O B. Credit Score =+OBalance 643 17,400 0.57 Oc. Credit Score =+OBalance + ( Utlization 526 13 27,100 0.78 814 22 13,500 0.05 OD. Credit Score + DUiliation 766 4 11,300 0.72 OE. Credit Score +OYears + DUlization OF. Credit Score =•OYears + (Balance • DUtilization 558 4 2,600 0.98 620 8 8,500 0.35 645 14 16, 100 0.23 691 3,400 0.11 OG. Credit Score DYears 652 13 7,600 0.05 698 17 20,400 0.24 704 11,800 0.13 638 6. 29,200 0.85 510 3 2,100 1.00
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:The accompanying Credit Approval Decisions data 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.
E Click the icon to view the Credit Approval Decisions data.
i........
Credit approval decisions data table
.....
What is the best model using the p-value criteria? Select the best answer below and fill in the answer boxes to complete your choice.
(Type integers or decimals rounded to three decimal places as needed.)
Revolving
Utilization (%)
Credit Score Years of Credit
Revolving
Balance (S)
History
O A. Credit Score =
) Years + (O Balance
728
21
11,420
0.23
VB. Credit Score = 760.800 + (- 219.013) Utilization
576
8
7,300
0.71
680
13
20,100
0.52
O C. Credit Score =
O Balance
628
17
12,900
0.68
530
10
5,800
0.77
O D. Credit Score =
O Years
798
21
9,100
0.14
O E. Credit Score =
+ (O Years + () Balance + (DUtilization
35,300
736
6
0.22
623
6
22,900
0.64
O F. Credit Score =
+ (
Balance + (DUtilization
594
18
16,600
0.51
+O Years + ( Utilization
9,300
O G. Credit Score =
663
22
0.34
703
18
22,100
0.16
What is the best model using the t-statistic criteria? Select the best answer below and fill in the answer boxes to complete your choice.
503
15
12,600
0.84
568
7
7,800
0.72
(Type integers or decimals rounded to three decimal places as needed.)
623
4
37,500
0.88
O A. Credit Score =
Years + (DBalance
777
12
6,200
0.08
805
11
10,600
0.04
O B. Credit Score =
Balance
+
643
8
17,400
0.57
O C. Credit Score =
Balance +
Utilization
526
13
27,100
0.78
+
814
22
13,500
0.05
O D. Credit Score =
Utilization
+
766
4
11,300
0.72
O E. Credit Score =
Years +
Utilization
558
4
2,600
0.98
+
620
8
8,500
0.35
O F. Credit Score =
Years + (DBalance +
Uilization
+
645
14
16,100
0.23
691
2
3,400
0.11
O G. Credit Score =
Years
+
652
13
7,600
0.05
698
17
20,400
0.24
704
8
11,800
0.13
638
6
29,200
0.85
510
3
2,100
1.00
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman