#36: Consider the data in the table below.

a) Examine the data and identify the relationship between x and y.

b) Find the linear correlation coefficient and use it to determine whether there appears

to be a significant linear correlation between x and y.

c) Construct a scatterplot. What does it suggest about the relationship between x and y?

d) Construct a residual plot. Are there any noticeable patterns? What does the residual

plot suggest about the relationship between x and y?

x 0 1 2 3 4 5 6 7 8 9 10

y 0 1 4 9 16 25 36 49 64 81 100

#16: Car Weight and Fuel Consumption Listed below are the weights (in pounds) and the highway fuel consumption amounts (in mi/gal) of randomly selected cars (Chrysler

Sebring, Ford Mustang, BMW 3-Series, Ford Crown Victoria, Honda Civic. Mazda

Protege, Hyundai Accent). Is there a linear correlation between weight and highway

fuel consumption? What does the result suggest about a national program to reduce

the consumption of imported oil?

Weight 3175 3450 3225 3985 2440 2500 2290

Fuel consumption 27 29 27 24 37 34 37

#16. Car Weight and Fuel Consumption. Find the best predicted highway full consumption amount (in mi/gal) for a car that weighs 3000 lb.

Weight 3175 3450 3225 3985 2440 2500 2290

Fuel consumption 27 29 27 24 37 34 37

#30. Appendix B Data Set: Discarded Plastic and Household Size Refer to Data Set 10

Appendix B and use the weights of discarded plastic and the corresponding house sizes. Find the best predicted household size given that the household discards 5 of plastic.

#30. Appendix B Data Set: Discarded Plastic and Household Size Refer to Data Set in Appendix B and use the weights of discarded plastic and the corresponding house

Price: $32.95

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