Question

Suppose the athletic director at a local university would like to develop a regression model to predict the point differentiaa. Check for the presence of multicollinearity Find the variance inflation factor (VIF) for each independent variable. Indeped. Identify the regression equation for the model in part c. Let y be the predicted point dferential. Select the correct choiGame   Point_Differential   Assists   Rebounds   Turnovers   Personal_Fouls
1   15   15   38   11   9
2   36   20   43   8   13
3   16   21   29   7   13
4   45   22   46   11   11
5   12   11   40   7   22
6   -10   10   31   13   26
7   11   19   45   11   7
8   12   16   32   16   14
9   3   16   27   18   15
10   19   9   34   17   17
11   40   16   41   9   17
12   44   12   29   9   22
13   16   17   36   13   20
14   12   21   21   9   22
15   11   14   34   19   23
16   14   20   36   18   12
17   8   12   42   14   17
18   -2   8   31   8   18
19   11   15   26   10   10
20   -15   10   48   11   26
21   -3   12   20   9   17
22   5   13   28   12   18
23   16   12   26   8   18
24   -1   16   27   12   19
25   -3   6   33   12   23
26   3   13   36   20   17
27   2   7   44   13   13
28   -5   14   30   12   15
29   -13   17   23   12   21
30   -21   18   19   9   18
31   -10   4   22   8   21
32   -1   6   21   9   22
33   -4   10   33   8   19
34   23   16   39   8   22
35   38   19   43   15   22
36   1   9   42   16   26
37   6   12   38   13   17
38   12   8   45   22   19
39   18   17   27   13   26
40   19   14   39   13   15
41   9   19   42   14   24
42   8   16   39   16   25
43   -10   12   24   9   19
44   38   19   44   10   19
45   34   15   39   12   17
46   2   13   31   7   17
47   27   19   38   14   19
48   2   17   24   12   20
49   8   10   34   21   33
50   5   16   36   11   27
51   26   14   49   12   20
52   10   10   34   20   20
53   18   20   30   11   23
54   10   15   43   13   16
55   -13   11   26   17   38
56   7   11   37   18   24
57   11   18   41   15   23
58   -9   9   26   9   30
59   -5   8   30   13   26
60   25   9   33   10   17
61   -18   15   36   16   25
62   4   14   28   12   22
63   -2   16   32   15   24
64   -4   13   27   14   17
65   3   9   26   16   19
66   -7   9   31   7   18

*ANSWERS ALREADY IN THE BOXES ARE INCORRECT*

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Answer #1

The step-by-step instr uctions to obtain Multiple Regression utput using Minitab18 * Store the dependent variable (y), (A), (

SUMMARY OUTPUT Rearession Statistics MultipleR R Square Adjusted R Square Standard Error Observations ANOVA 0.970472691 0.941

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ct The multiple linear regression equation is -24.47705104+0.951328566X, +1.301241566 X2 0.201988848X3 -0.689030363X Step1 Th

Independent variable.X, Since, the test stati sti c is t-2.9815>0.105 2.015048 We reject the null hypothesis H,o Since, the P

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The 90% confidence interval for the coefficient of personal fouls independent variable is to From the above multiple regressi

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