A Traffic Consultant Has Analysed the Factors That Affect the Number

question 11

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: $y =$ $\beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 1 } ^ { 2 } + \beta _ { 4 } x _ { 2 } ^ { 2 } + \beta _ { 5 } x _ { 1 } x _ { 2 } + \varepsilon$ .
Where:
y = number of annual fatalities per shire. $x _ { 1 }$ = number of cars registered in the shire (in units of 10 000). $x _ { 2 }$ = 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 $y =$ $69.7 + 11.3 x _ { 1 } + 7.61 x _ { 2 } - 1.15 x _ { 1 } ^ { 2 } - 0.51 x _ { 2 } ^ { 2 } - 0.13 x _ { 1 } x _ { 2 }$ . $$\begin{array} { | c | r r c | } \hline \text { Predictor } & \text { Coef } & \text { SiDev } & T \\\hline \text { Constant } & 69.7 & 41.3 & 1.688 \\x _ { 1 } & 11.3 & 5.1 & 2.216 \\x _ { 2 } & 7.61 & 2.55 & 2.984 \\x _ { 1 } ^ { 2 } & - 1.15 & 0.64 & - 1.797 \\x _ { 2 } ^ { 2 } & - 0.51 & 0.20 & - 2.55 \\x _ { 1 } x _ { 2 } & - 0.13 & 0.10 & - 1.30 \\\hline\end{array}$$ S = 15.2 R-Sq = 47.2%.
ANALYSIS OF VARIANCE $$\begin{array} { | l | c c c c | } \hline \begin{array} { l } \text { Source of } \\\text { Variation }\end{array} & d f & \text { SS } & M S & F \\\hline \text { Regression } & 5 & 5959 & 1191.800 & 5.181 \\\text { Error } & 29 & 6671 & 230.034 & \\\hline \text { Total } & 34 & 12630 & & \\\hline\end{array}$$ Is there enough evidence at the 5% significance level to conclude that the model is useful in predicting the number of fatalities?

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Officially recorded and recognized by authorities or organizations.

Attack Rate

is the percentage of an at-risk population that contracts a disease during a specified time period, often used in the context of an outbreak.