Plz answer all the questions i'm boutta fail this class

Suppose that for a typical FedEx package delivery, the cost ofthe shipment is a function of the weight of the package. You findout that the regression equation for this relationship is (cost ofdelivery) = 3.603*(weight) + 4.733. If a package you want to shipweighs 44 ounces, what would you expect to pay for theshipment?

A. 163.27

B.158.53

C.We do not know the observations in the data set, so we cannotanswer that question.

D.10.9

E. 211.85

Suppose that for a typical FedEx package delivery, the cost ofthe shipment is a function of the weight of the package. You findout that the regression equation for this relationship is (cost ofdelivery) = 1.971*(weight) + 7.071. Interpret the slope.

A.When weight increases by 1 pound, cost of delivery increasesby 7.071 dollars.

B.We are not given the dataset, so we cannot make aninterpretation

C.When cost of delivery increases by 1 dollar, weight increasesby 1.971 pounds.

D.When cost of delivery increases by 1 dollar, weight increasesby 7.071 pounds.

E. When weight increases by 1 pound, cost of delivery increasesby 1.971 dollars.

Suppose that a researcher studying the weight of female collegeathletes wants to predict the weights based on height, measured ininches, and the percentage of body fat of an athlete. Theresearcher calculates the regression equation as (weight) =4.459*(height) + 0.85*(percent body fat) - 89.236. If a femaleathlete is 61 inches tall, has a 22 percentage of body fat, and aweight of 166.425, the residual is -35.038. Choose the correctinterpretation of the residual.

A. The weight of the athlete is 35.038 pounds less than what wewould expect.

B. The height of the athlete is 35.038 inches less than what wewould expect.

C. The height of the athlete is 35.038 inches larger than whatwe would expect.

D.The weight of the athlete is 166.425 pounds less than what wewould expect.

E.The weight of the athlete is 35.038 pounds greater than whatwe would expect.

While attempting to measure its risk exposure for the upcomingyear, an insurance company notices a trend between the age of acustomer and the number of claims per year. It appears that thenumber of claims keep going up as customers age. After performing aregression, they find that the relationship is (claims per year) =0.28*(age) + 5.17. If a customer is 41 years old and they make anaverage of 12.95 claims per year, what is the residual?

A.24.35

B.-28.05

C.3.7

D.28.05

E. -3.7

Suppose that in a certain neighborhood, the cost of a home (inthousands) is proportional to the size of the home in square feet.The regression equation quantifying this relationship is found tobe (price) = 0.024*(size) + 39.993. You look more closely at one ofthe houses selected. The house is listed as having 2033.702 squarefeet and is listed at a price of $104.498 (thousand). The residualis 15.696. Interpret this residual in terms of the problem.

A.The price of the house is 15.696 thousand dollars larger thanwhat we would expect.

B. The price of the house is 104.498 thousand dollars largerthan what we would expect.

C. The price of the house is 15.696 thousand dollars less thanwhat we would expect.

D. The square footage is 15.696 square feet larger than what wewould expect.

E. The square footage is 15.696 square feet less than what wewould expect.

Suppose that a researcher studying the weight of female collegeathletes wants to predict the weights based on height, measured ininches, and the percentage of body fat of an athlete. Theresearcher calculates the regression equation as (weight) =4.715*(height) + 1.108*(percent body fat) - 90.653. If a femaleathlete is 63 inches tall and has a 15 percentage of body fat, whatis her expected weight?

A. Not enough information

B. 404.318

C.313.665

D. 49.876

E.223.012

Suppose the sales (1000s of $) of a fast food restaurant are alinear function of the number of competing outlets within a 5 mileradius and the population (1000s of people) within a 1 mile radius.The regression equation quantifying this relation is (sales) =1.526*(competitors) + 6.09*(population) + 7.226. Suppose the sales(in 1000s of $) to be of a store that has 5 competitors and apopulation of 7 thousand people within a 1 mile radius are 54.151(1000s $). What is the residual?

A. -3.335

B. 52.486

C. 3.335

D. Not enough information