Linear Regression Case Study: Predicting Winnings for NASCAR Drivers

Please reference the photo and attached excel file. Complete the work on the excel file or post answer with how it should be inputted into the excel file. 

1. Suppose you wanted to predict Winnings ($) using only the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), or the number of top ten finishes (Top 10). Which of these four variables provides the best single predictor of winnings?
2. Develop an estimated regression equation that can be used to predict Winnings ($) given the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), and the number of top ten finishes (Top 10). Test for individual significance and discuss your findings and conclusions. 
3. Create two new independent variables: Top 2–5 and Top 6–10. Top 2–5 represents the number of times the driver finished between second and fifth place and Top 6–10 represents the number of times the driver finished between sixth and tenth place. Develop an estimated regression equation that can be used to predict Winnings ($) using Poles, Wins, Top 2–5, and Top 6–10. Test for individual significance and discuss your findings and conclusions.
4. Based upon the results of your analysis, what estimated regression equation would you recommend using to predict Winnings ($)? Provide an interpretation of the estimated regression coefficients for this equation.

2

>Data

0

1
5

,529,

0

2403
3
1
19

0
4
9
19

0

3
3

3,580

1
3

14

0
2
14

1
0
4
12

3,690

1
3

18

0
1
5
14

2284
3
1
9

3
2
8
16

,470

1
4
14
18

0
1
4
16

2
1
8

0
0
1
10

3
0
3
10

0
1
4
8

1
0
3
12

936
0
1
5
12

0
0
2
5

2
0
2
8

2
0
2
10

2
1
4
8

2
0
4
6

0
0
3
7

0
1
2
5

1
0
2
4

1
0
1
3

0
0
1
2

0
0
1
2

0
0
0
0

0
0
1
1

0
0
0
0

0
0
0
0

0
0
0
0