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Question: The president of a company that manufactures drywall wants to analyze the variables that affect demand for his product.  Drywall is used to construct walls in houses and offices. Consequently, the president decides to develop a regression model in which the dependent variable is monthly sales of drywall (in hundreds of 4x8 sheets and the independent variables are

Number of building permits issued in the county

Five year mortgage rates (in percentage points)

Vacancy rate in apartments (in percentage points)

To estimate a multiple regression model, he took monthly observations from the past 2 years.

a) Analyze the data using multiple regression

b) What is the standard error of estimate? Can you use this statistic to assess the model's fit?  If so, how?

c) What is the coefficient of determination, and what does it tell you about the regression model?

d) Test the overall validity of the model

e) Interpret each of the coefficients

f) Test to determine whether each of the independent variables is linearly related to drywall demand in this model

g) Predict next month's drywall sales with 95% confidence if the number of building permits is 50,the 5-year mortgage rate is 9.0% and the vacancy rates are 3.6% in apartments and 14.3% in office buildings.

Drywall

Permits

Mortgage

A Vacancy

O Vacancy


328

49

8.35

2.98

13.43


376

79

8.08

5.6

14.51


373

79

7.9

2.25

14.24


144

50

7.69

4.26

14.3


194

37

7

2.6

11.64


220

53

7.32

2.97

10.61


126

22

8.4

5.35

18.45


301

69

8.28

3.13

18.52


54

21

8

5.6

10.29


252

46

8.95

4.81

11.91


381

79

8.21

5.88

17.75


173

30

7.24

2.98

18.16


152

38

7.35

5.69

17.14


351

73

7.27

4.86

16.11


233

55

7.08

5.68

18.54


35

12

7.76

4.46

19.46


290

62

8.21

2.23

19.26


5

12

7.76

5

17.28


335

60

7.2

2.42

15.15


280

49

7.57

3.25

19.94


101

14

8.44

3.61

15.47


297

66

8.43

2.13

12.75


309

62

8.14

4.35

12.24


233

40

8.81

2.31

18.65


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