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

\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 + 11.3 x _ { 1 } + 7.61 x _ { 2 } - 1.15 x _ { 1 } ^ { 2 } - 0.51 x _ { 2 } ^ { 2 } - 0.13 x _ { 1 } x _ { 2 }

\begin{array}{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= 15.2 \quad \mathrm { R } - \mathrm { Sq } = 47.2 \%

ANALYSIS OF VARIANCE

\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

x _ { 2 } ^ { 2 }

term should be retained in the model.

Suppose That the Sample Regression Equation of a Second-Order Model y~=2.50+0.15x+0.45x2\tilde { y } = 2.50 + 0.15 x + 0.45 x ^ { 2 }y~​=2.50+0.15x+0.45x2

Multiple Choice

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Suppose That the Sample Regression Equation of a Second-Order Model $\tilde { y } = 2.50 + 0.15 x + 0.45 x ^ { 2 }$

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