I need help answering these questions. I keep getting incorrect answers.

The regression model Yi=417.16+468.51X1i3.01X2i predicts appraised value(in thousands ofdollars) based on land area of the property(in acres), X1i, and age(in years), X2i, of thesingle-family home i. The data from which the model was constructed are provided. Use the regression model and the data to complete the following questions.

Home, Appraised Value_($thousands), Land_Area, Age

1 468.7 0.2244 49

2 360.8 0.2193 56

3 421.6 0.1653 27

4 543.8 0.4617 19

5 402.1 0.2574 43

6 373.4 0.2297 80

7 319.1 0.1888 40

8 742.2 0.5072 10

9 211.6 0.2269 50

10 635.8 0.1343 11

11 348.7 0.1714 53

12 354.1 0.4257 48

13 350.4 0.2568 48

14 277.3 0.1196 19

15 308.9 0.1611 62

16 285.5 0.1746 53

17 393.4 0.3867 49

18 619.4 0.6529 47

19 317.8 0.1722 60

20 360.2 0.1498 80

a. Perform a residual analysis on the results.

Plot the residuals versus Yi.

Plot the residuals versus X1i.

Plot the residuals versus X2i.

Make a conclusion regarding the regression model. Choose the correct answer below.

A.

There is no particular pattern in the plots. The model appears to be adequate.

B.

There appears to be a quadratic relationship in each of the residual plots. The model appears to be adequate.

C.

There is no particular pattern in the plots. The model is not adequate.

D.

There appears to be a quadratic relationship in each of the residual plots. The model is not adequate.

Is it necessary to test the assumption of independence of errors

A.

No, this is not a time series data.

B.

Yes, this is a time series data.

Are the regression assumptions of linearity and equal variance valid for thesedata?

A.

Yes, because there is no particular pattern in the residual plots.

B.

Yes, because there is a pattern in the residual plots.

C.

No, because there is a pattern in the residual plots.

D.

No, because there is no particular pattern in the residual plots.