Question 10 (1 point) Suppose the sales (1000s of $) of a fast food restaurant a

Question

Question 10 (1 point)

Suppose the sales (1000s of $) of a fast food restaurant are a linear function of the number of competing outlets within a 5 mile radius and the population (1000s of people) within a 1 mile radius. The regression equation quantifying this relation is (sales) = 1.738*(competitors) + 5.953*(population) + 6.602. Suppose the sales (in 1000s of $) to be of a store that has 5.529 competitors and a population of 7.394 thousand people within a 1 mile radius are 52.684 (1000s $). You calculate the residual to be 7.544. What is the best interpretation of this residual?

Question 10 options:

1)

2)

3)

4)

5)

Question 11 (1 point)

A trucking company considered a multiple regression model for relating the dependent variable of total daily travel time for one of its drivers (hours) to the predictors distance traveled (miles) and the number of deliveries of made. After taking a random sample, a multiple regression was performed and the equation is (time) = 0.05*(distance) + 0.79*(deliveries) - 1.045. Suppose for a given driver's day, he is scheduled to drive 229.005 miles and make 8.273 stops. Suppose it took him 16.185 hours to complete the trip. What is the residual based on the regression model?

Question 11 options:

1)

2)

3)

4)

5)

1)

The number of competitors are 7.544 stores less than what we would expect.

2)

The sales are 52.684 (1000s $) larger than what we would expect.

3)

The sales are 7.544 (1000s $) less than what we would expect.

4)

The number of competitors are 7.544 stores larger than what we would expect.

5)

The sales are 7.544 (1000s $) larger than what we would expect.

Explanation / Answer

Correct option is 1)

for the given condition of the man we would expect max oxygen intake for the man to be 60.227

And we observed max oxygen intake of 52.684

since we know that

residual = observed quantity - expected quantity

So option 2 is correct

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