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An Avid Football Fan Was in the Process of Examining y=β0+β1x+β2x2+εy = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 } + \varepsilon

question 37

Essay

An avid football fan was in the process of examining the factors that determine the success or failure of football teams. He noticed that teams with many rookies and teams with many veterans seem to do quite poorly. To further analyse his beliefs, he took a random sample of 20 teams and proposed a second-order model with one independent variable. The selected model is: y=β0+β1x+β2x2+εy = \beta _ { 0 } + \beta _ { 1 } x + \beta _ { 2 } x ^ { 2 } + \varepsilon .
where
y = winning team's percentage.
x = average years of professional experience.
The computer output is shown below:
THE REGRESSION EQUATION IS: y=y = 32.6+5.96x0.48x232.6 + 5.96 x - 0.48 x ^ { 2 }  Predictor  Coef  SyDev  T  Constant 32.619.31.689x5.962.412.473x20.480.222.182\begin{array} { | c | r r r | } \hline \text { Predictor } & \text { Coef } & \text { SyDev } & \text { T } \\\hline \text { Constant } & 32.6 & 19.3 & 1.689 \\x & 5.96 & 2.41 & 2.473 \\x ^ { 2 } & - 0.48 & 0.22 & - 2.182 \\\hline\end{array} S = 16.1 R-Sq = 43.9%.
ANALYSIS OF VARIANCE  Source of Variation df SS MSF Regression 2345217266.663 Error 174404259.059 Total 197856\begin{array} { | l | c c c c | } \hline \text { Source of Variation } & d f & \text { SS } & M S & F \\\hline \text { Regression } & 2 & 3452 & 1726 & 6.663 \\\text { Error } & 17 & 4404 & 259.059 & \\\hline \text { Total } & 19 & 7856 & & \\\hline\end{array} Test to determine at the 10% significance level if the linear term should be retained.


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