I will make this worth your time if you answer these followi

I will make this worth your time if you answer these following questions- 750 pts awarded!

Question 1

The following situation will be used for Questions 1-7:

Select one:

a. The data has a linear, weak, and negative relationship.

b. The data has a linear, strong, and positive relationship.

c. The data has a curved, strong, and negative relationship.

d. The data has a linear, weak, and positive relationship.

Question 2

What is the value of correlation coefficient r for the relationship between selling price and size?

Select one:

a. 0.5488

b. 0.6352

c. 0.7783

d. 0.9006

e. 0.9982

Question 3

What is the equation of the regression line?

Select one:

a. selling price = -39.806084 + 0.099197954*size

b. size = -39.806084 + 0.099197954*selling price

c. selling price = 0.099197954 - 39.806084*size

d. size = 0.099197954 - 39.806084*selling price

Question 4

Suppose the slope of the regression line is 8.9904. What does this slope mean in context of the problem?

Select one:

a. On average, if the size of a house increases by 1 square foot we would expect the price of the house to increase by 8.9904 thousands of dollars.

b. On average, if the size of a house increases by 8.9904 square feet we would expect the price of the house to increase by one thousand of dollars.

c. If the size of a house increases by 1 square foot we know the the price of the house will increase by 8.9904 thousands of dollars.

d. When the average size of a house is 0 square feet we would expect this house to sell for 8.9904 thousands of dollars.

Question 5

Suppose the y-intercept of the regression equation is -22.000. What does this y-intercept mean in context of the problem?

Select one:

a. When the average size of a house is 0 square feet we would expect this house to sell for -22.000 thousands of dollars.

b. When the average size of a house is -22.000 square feet we would expect this house to sell for 0 thousands of dollars.

c. On average, as the size of house increases by 1 square foot we would expect the price of the house to decrease by -22.000 thousands of dollars.

d. All houses that are 0 square feet will definitely sell for -22.000 thousands of dollars.

Question 6

If a house is 2530 square feet in size, what will be its predicted selling price (in thousands of dollars)?

Select one:

a. $211.16

b. $200.19

c. $215.48

d. $213.23

Question 7

Should we use this regression line to predict the price of a house that is 6000 square feet in size? Why or why not?

Select one:

a. Yes, it would be helpful to know how much a 6000 square foot house would cost.

b. No, that would be extrapolating beyond the range of our data which we should never do.

c. Yes,whenever we can we should extrapolate beyond the range of our data.

d. No, houses that are 6000 square feet do not cost any money.

Solution

1)c. The data has a curved, strong, and negative relationship.

2)b. 0.6352

3)d. size = 0.099197954 - 39.806084*selling price

4)d. When the average size of a house is 0 square feet we would expect this house to sell for 8.9904 thousands of dollars.

5)c. On average, as the size of house increases by 1 square foot we would expect the price of the house to decrease by -22.000 thousands of dollars.

6)b. $200.19

7)c. Yes,whenever we can we should extrapolate beyond the range of our data.