Question

In: Statistics and Probability

The National Football League (NFL) records a variety of performance data for individuals and teams. To...

The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference (Conf), average number of passing yards per attempt (Yds/Att), the number of interceptions thrown per attempt (Int/Att), and the percentage of games won (Win%) for a random sample of 16 NFL teams for the 2011 season (NFL web site, February 12, 2012).

Click on the datafile logo to reference the data.

Team Conference Yds/Att Int/Att Win%
Arizona Cardinals NFC 6.5 0.042 50.0
Atlanta Falcons NFC 7.1 0.022 62.5
Carolina Panthers NFC 7.4 0.033 37.5
Cincinnati Bengals AFC 6.2 0.026 56.3
Detroit Lions NFC 7.2 0.024 62.5
Green Bay Packers NFC 8.9 0.014 93.8
Houstan Texans AFC 7.5 0.019 62.5
Indianapolis Colts AFC 5.6 0.026 12.5
Jacksonville Jaguars AFC 4.6 0.032 31.3
Minnesota Vikings NFC 5.8 0.033 18.8
New England Patriots AFC 8.3 0.020 81.3
New Orleans Saints NFC 8.1 0.021 81.3
Oakland Raiders AFC 7.6 0.044 50.0
San Francisco 49ers NFC 6.5 0.011 81.3
Tennessee Titans AFC 6.7 0.024 56.3
Washington Redskins NFC 6.4 0.041 31.3

Let x1 represent Yds/Att.
Let x2 represent Int/Att.

(a) Develop the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ =   +  x1
What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.
%
(b) Develop the estimated regression equation that could be used to predict the percentage of games won, given the number of interceptions thrown per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ =   +  x2
What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.
%
(c) Develop the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt and the number of interceptions thrown per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ =   +  x1 +  x2
What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.
%
(d) The average number of passing yards per attempt for the Buffalo Bills during the 2011 season was 6.7, and the team’s number of interceptions thrown per attempt was 0.043. Use the estimated regression equation developed in part (c) to predict the percentage of games won by the Buffalo Bills during the 2011 season. (Note: For the 2011 the 2011 season, the Buffalo Bills' record was 7 wins and 9 loses.)
If required, round your answer to one decimal digit. Do not round intermediate calculations.
%
Compare your prediction to the actual percentage of games won by the Buffalo Bills. If required, round your answer to one decimal digit.
The Buffalo Bills performed - Select your answer -better worse Item 12  than what we predicted by  %.
(e) Did the estimated regression equation that uses only the average number of passing yards per attempt as the independent variable to predict the percentage of games won provide a good fit?
The input in the box below will not be graded, but may be reviewed and considered by your instructor.

Solutions

Expert Solution

using excel>data>data analysis>Regression

we have

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.759693
R Square 0.577133
Adjusted R Square 0.546928
Standard Error 15.87319
Observations 16
ANOVA
df SS MS F Significance F
Regression 1 4814.254 4814.254 19.10735 0.000639
Residual 14 3527.416 251.9583
Total 15 8341.67
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -58.7703 26.17541 -2.24525 0.041423 -114.911 -2.62964
Yds/Att 16.39063 3.749689 4.371195 0.000639 8.348341 24.43291
(a) the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ = -58.770 + 16.391 x1
What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.
57.7%
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.661739
R Square 0.437898
Adjusted R Square 0.397748
Standard Error 18.3008
Observations 16
ANOVA
df SS MS F Significance F
Regression 1 3652.8 3652.8 10.90651 0.005236
Residual 14 4688.87 334.9193
Total 15 8341.67
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 97.53825 13.86182 7.03647 5.9E-06 67.80762 127.2689
Int/Att -1600.49 484.63 -3.3025 0.005236 -2639.92 -561.063
(b) Develop the estimated regression equation that could be used to predict the percentage of games won, given the number of interceptions thrown per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ = 97.538+ -600.49 x2

What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.

43.8%

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.867461
R Square 0.752489
Adjusted R Square 0.71441
Standard Error 12.60237
Observations 16
ANOVA
df SS MS F Significance F
Regression 2 6277.014 3138.507 19.76145 0.000114
Residual 13 2064.656 158.8197
Total 15 8341.67
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -5.76328 27.1468 -0.2123 0.835165 -64.4104 52.88381
Yds/Att 12.94936 3.18567 4.064877 0.001338 6.067136 19.83158
Int/Att -1083.79 357.1165 -3.03483 0.009575 -1855.29 -312.285
(c) Develop the estimated regression equation that could be used to predict the percentage of games won, given the average number of passing yards per attempt and the number of interceptions thrown per attempt. If required, round your answer to three decimal digits. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)
ŷ = -5.763 + 12.949 x1 + -1083.79 x2

What proportion of variation in the sample values of proportion of games won does this model explain? If required, round your answer to one decimal digit.

75.3%

(d) The average number of passing yards per attempt for the Buffalo Bills during the 2011 season was 6.7, and the team’s number of interceptions thrown per attempt was 0.043. Use the estimated regression equation developed in part (c) to predict the percentage of games won by the Buffalo Bills during the 2011 season. (Note: For the 2011 the 2011 season, the Buffalo Bills' record was 7 wins and 9 loses.)
ŷ = -5.763 + 12.949*6.7 + -1083.79*0.043
=34.4 %
(e) Did the estimated regression equation that uses only the average number of passing yards per attempt as the independent variable to predict the percentage of games won provide a good fit?
yes

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