Question

How does the fuel consumption of a car change as its speed increases? Here are data for a British Ford Escort. Speed is measured in kilometers per hour, and fuel consumption is measured in liters of gasoline used per 100 kilometers traveled.

Speed Fuel 40 10 20 30 50 60 70 80 21.00 13.00 10.00 8.00 7.00 5.90 6.30 6.95 Speed Fuel 90 100 110 120 130 140 150 8.27 9.03 9.87 10.79 11.77 12.83 7.57

(a) Make a scatterplot. (Do this on paper. Your instructor may ask you to turn in this work.)

What is the explanatory variable?
The explanatory variable is: (choose one of the following)

1. car model

2. fuel consumption

3. speed

4. time

(b) Describe the form of the relationship. It is not linear. Explain why the form of the relationship makes sense. (choose one of the following options)

1. The relationship is curved--low in the middle, higher at the extremes because high fuel efficiency is actually good (it means that we use less fuel to travel 100 km), this makes sense: moderate speeds yield the best performance.

2. The relationship is curved--high in the middle, lower at the extremes because low fuel efficiency is actually good (it means that we use more fuel to travel 100 km), this makes sense: moderate speeds yield the worst performance.

3. The relationship is curved--low in the middle, higher at the extremes because high fuel efficiency is actually bad (it means that we use more fuel to travel 100 km), this makes sense: moderate speeds yield the worst performance.

(c) Does it make sense to describe the variables as either positively associated or negatively associated? (yes or no)

Why? (explain)

(d) Is the relationship reasonably strong or quite weak?

Explain your answer.   

Answer 1

Fuel 0 20 40 60 80 100 120 140 15 speed in Speed PS explanatory variabile. The relationship is curred - low middle higher at extremes. since low mpleage is acually option) good yes, average values of mileage are found with both low & high values of Speeds! C positively associated - Speed Neg. assoc. - Low speed) relationship is very strong there is little scatter around the curve, & it is very useful for prediction d) The