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A Trucking Company Considered a Multiple Regression Model for Relating x1x _ { 1 }

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A trucking company considered a multiple regression model for relating the dependent variable y=total daily travel time for one of its drivers (hours) to the predictors x1x _ { 1 } =distance traveled (miles) and x2x _ { 2 } the number of deliveries made. Suppose that the model equation is Y=.800+.062x1+.900x2+εY = - .800 + .062 x _ { 1 } + .900 x _ { 2 } + \varepsilon
a. What is the mean value of travel time when distance traveled is 50 miles and three deliveries are made?
b. How would interpret β1=.060\beta _ { 1 } = .060 \text {, }
the coefficient of the predictor x1x _ { 1 }
? What is the interpretation of β2=.900?\beta _ { 2 } = .900 ?
c. If σ=.5\sigma = .5
hour, what is the probability that travel time will be at most 6 hours when three deliveries are made and the distance traveled is 50 miles?


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