Question

In: Statistics and Probability

Use the “home” data to build a regression model that predicts market as a function of...

Use the “home” data to build a regression model that predicts market as a function of square feet. Is the coefficient for square feet significant at a .05 level?

Home Market Value
House Age Square Feet Market Value
33 1,812 $90,000.00
32 1,914 $104,400.00
32 1,842 $93,300.00
33 1,812 $91,000.00
32 1,836 $101,900.00
33 2,028 $108,500.00
32 1,732 $87,600.00
33 1,850 $96,000.00
32 1,791 $89,200.00
33 1,666 $88,400.00
32 1,852 $100,800.00
32 1,620 $96,700.00
32 1,692 $87,500.00
32 2,372 $114,000.00
32 2,372 $113,200.00
33 1,666 $87,500.00
32 2,123 $116,100.00
32 1,620 $94,700.00
32 1,731 $86,400.00
32 1,666 $87,100.00
28 1,520 $83,400.00
27 1,484 $79,800.00
28 1,588 $81,500.00
28 1,598 $87,100.00
28 1,484 $82,600.00
28 1,484 $78,800.00
28 1,520 $87,600.00
27 1,701 $94,200.00
28 1,484 $82,000.00
28 1,468 $88,100.00
28 1,520 $88,100.00
27 1,520 $88,600.00
27 1,484 $76,600.00
28 1,520 $84,400.00
27 1,668 $90,900.00
28 1,588 $81,000.00
28 1,784 $91,300.00
27 1,484 $81,300.00
27 1,520 $100,700.00
28 1,520 $87,200.00
27 1,684 $96,700.00
27 1,581 $120,700.00

Solutions

Expert Solution

Use the “home” data to build a regression model that predicts market as a function of square feet. Is the coefficient for square feet significant at a .05 level?

Excel Addon Megastat used.

Menu used: correlation/Regression ---- Regression Analysis.

The regression line is Market Value=32,673.220+35.036* square foot

t =35.036/5.167 =  6.78, P=0.0000 which is < 0.05 level of significance. Ho is rejected.
 

There is enough evidence to conclude that coefficient for square feet significant at a .05 level.

Regression Analysis

0.535

n

42

r

0.731

k

1

Std. Error of Estimate

7287.723

Dep. Var.

Market Value

Regression output

confidence interval

variables

coefficients

std. error

   t (df=40)

p-value

95% lower

95% upper

Intercept

a =

32,673.220

Square Feet

b =

35.036

5.167

6.780

0.0000

24.593

45.480

ANOVA table

Source

SS

df

MS

F

p-value

Regression

2,441,633,668.922

1  

2,441,633,668.922

45.97

0.0000

Residual

2,124,436,092.983

40  

53,110,902.325

Total

4,566,069,761.905

41  


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