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A Traffic Consultant Has Analysed the Factors That Affect the Number

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Essay

A traffic consultant has analysed the factors that affect the number of traffic fatalities. She has come to the conclusion that two important variables are the number of cars and the number of tractor-trailer trucks. She proposed the second-order model with interaction: y=y = β0+β1x1+β2x2+β3x12+β4x22+β5x1x2+ε\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 .
Where:
y = number of annual fatalities per shire. x1x _ { 1 } = number of cars registered in the shire (in units of 10 000). x2x _ { 2 } = number of trucks registered in the shire (in units of 1000).
The computer output (based on a random sample of 35 shires) is shown below.
THE REGRESSION EQUATION IS y=y = 69.7+11.3x1+7.61x21.15x120.51x220.13x1x269.7 + 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  SiDev T Constant 69.741.31.688x111.35.12.216x27.612.552.984x121.150.641.797x220.510.202.55x1x20.130.101.30\begin{array} { | c | r r c | } \hline \text { Predictor } & \text { Coef } & \text { SiDev } & 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 & 0.64 & - 1.797 \\x _ { 2 } ^ { 2 } & - 0.51 & 0.20 & - 2.55 \\x _ { 1 } x _ { 2 } & - 0.13 & 0.10 & - 1.30 \\\hline\end{array} S = 15.2 R-Sq = 47.2%.
ANALYSIS OF VARIANCE  Source of  Variation df SS MSF Regression 559591191.8005.181 Error 296671230.034 Total 3412630\begin{array} { | l | c c c c | } \hline \begin{array} { l } \text { Source of } \\\text { Variation }\end{array} & d f & \text { SS } & M S & F \\\hline \text { Regression } & 5 & 5959 & 1191.800 & 5.181 \\\text { Error } & 29 & 6671 & 230.034 & \\\hline \text { Total } & 34 & 12630 & & \\\hline\end{array} Test at the 1% significance level to determine whether the x1x _ { 1 } term should be retained in the model.


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