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Motorcycle Fatalities
a Traffic Consultant Has Analyzed the Factors That

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Motorcycle Fatalities
A traffic consultant has analyzed the factors that affect the number of motorcycle fatalities.She has come to the conclusion that two important variables are the number of motorcycle and the number of cars.She proposed the model y~=β0+β1x1+β2x2+β3x12+β4x22+β5x1x2+ε\tilde { y } = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } ^ { 2 } + \beta _ { 4 } x _ { 2 } ^ { 2 } + \beta _ { 5 } x _ { 1 } x _ { 2 } + \varepsilon (the second-order model with interaction),where y = number of annual fatalities per county,x1 = number of motorcycles registered in the county (in 10,000),and x2 = number of cars registered in the county (in 1000).The computer output (based on a random sample of 35 counties)is shown below:
THE REGRESSION EQUATION IS y=69.7+11.3x1+7.61x21.15x120.51x220.13x1x2y = 69.7 + 11.3 x _ { 1 } + 7.61 x _ { 2 } - 1.15 x _ { 1 } ^ { 2 } - 0.51 x _ { 2 } ^ { 2 } - 0.13 x _ { 1 } x _ { 2 }  Predictor Coef  StDev T Constant69.741.31.688x111.35.12.216x27.612.552.984x121.15.641.797x22.51.202.55x1x2.13.101.30\begin{array}{ccc}\text { Predictor}&\text { Coef } & \text { StDev } & T \\\hline\text { Constant}& 69.7 & 41.3 & 1.688 \\x_{1} &11.3 & 5.1 & 2.216 \\ x_{2}&7.61 & 2.55 & 2.984 \\x_1^2&-1.15 & .64 & -1.797 \\& & \\x_2^2&-.51 & .20 & -2.55 \\& & \\& & \\ x_{1} x_{2}&-.13 & .10 & -1.30\end{array} S=15.2RSq=47.2%S= 15.2 \quad \mathrm { R } - \mathrm { Sq } = 47.2 \% ANALYSIS OF VARIANCE
 Source of Variation dfSSMSF Repressian 559591191.8005.181 Error 296671230.034 Total 3412630\begin{array} { | l | c c c c | } \hline \text { Source of Variation } & \boldsymbol { df } & \mathbf { S S } & \boldsymbol { M S } & \boldsymbol { F } \\\hline \text { Repressian } & 5 & 5959 & 1191.800 & 5.181 \\\text { Error } & 29 & 6671 & 230.034 & \\\hline \text { Total } & 34 & 12630 & & \\\hline\end{array}
-{Motorcycle Fatalities Narrative} Test at the 1% significance level to determine if the x12x _ { 1 } ^ { 2 } term should be retained in the model.


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