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Data were collected to explain the number of wins an NFL team has based on the average points per game that they score (PPG) Based on the regression results, answer the following questions d) Is the coefficient on the variable “PPG” statistically significantly different than 0 at the 1% level of significance? How do you know? e) What is the predicted number of wins for a team that averages scoring 28 points per game? f) What is the effect on wins of increasing the average PPG by 1?

Data were collected to explain the number of wins an NFL team has based on the average points per game that they score (PPG) Based on the regression results, answer the following questions d) Is the coefficient on the variable “PPG” statistically significantly different than 0 at the 1% level of significance? How do you know? e) What is the predicted number of wins for a team that averages scoring 28 points per game? f) What is the effect on wins of increasing the average PPG by 1?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Data were collected to explain the number of wins an NFL team has based on the average points per game that they score (PPG) Based on the regression results, answer the following questions d) Is the coefficient on the variable “PPG” statistically significantly different than 0 at the 1% level of significance? How do you know? e) What is the predicted number of wins for a team that averages scoring 28 points per game? f) What is the effect on wins of increasing the average PPG by 1?
Complete the Table Below Regression Statistics Multiple R R Square Adjusted R Square 0.571 Standard Error Observations 11 ANOVA df SS MS F Significance F Regression 68.0 0.00430874 Residual 42.7 Total Upper 95% Standard Coefficients Error t Stat P-value Lower 95% Intercept -6.758 3.835 0.112 PPG 0.673 0.178 0.004
Transcribed Image Text:Complete the Table Below Regression Statistics Multiple R R Square Adjusted R Square 0.571 Standard Error Observations 11 ANOVA df SS MS F Significance F Regression 68.0 0.00430874 Residual 42.7 Total Upper 95% Standard Coefficients Error t Stat P-value Lower 95% Intercept -6.758 3.835 0.112 PPG 0.673 0.178 0.004
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