Question

A realtor examined effects of house size (in sq ft) and lot size (in sq ft) on house prices (in $).

The output is:

Regression Stats:
Multi R 0.747996973
R Sq 0.559499471
Adjusted R Sq 0.550416986
Standard Error 24907.48117
Observations 100

ANOVA
Regression: df 2, SS 76433650425, MS 3.82E+10, F 61.60202, Sig F 5.38768E-18
Residual: df 97, SS 60177113975, MS 6.2E+08
Total: df 99, SS 1.36611E+11

Intercept: Co-Eff 40715.70381, Standard Error 10826.31648, t.stat 3.760809, p-val 0.00029
House Size: Co-Eff 78.36771583, Standard Error 58.28252415, t.stat 1.528156, p-val 0.129728
Lot Size: Co-Eff -4.70191727, Standard Error 16.91483253, t.stat -0.27798, p-val 0.781622

a.) Find regression equation for the output.
b.) Find house size and lot size coefficients.
c.) Is the model valid? ___ p= ___
d.) What % of var in y does the model explain?
e.) What independent variable(s) is/are linearly related to dep.var and why?
f.) What type of variable would need to be added to control if the house is bungalow or 2-story. What value should the variable use?

Answer 1

a.) the regression equation for the output is

house price = 40715.70381+ 78.36771583*House size -4.70191727 lot size
b.) house size coefficients = 78.36771583

lot size coefficient =-4.70191727
c.) yes the model is valid because p value is less than 0.05 , p= 0.0000
d.) the model explain 55.95 % of var in y
e.) No independent variable(s) are linearly related to dep.var bacause their p value is more than 0.05 so they are equal to 0
f.) the dummy variable would need to be added to control if the house is bungalow or 2-story.

the value should the variable use ar 1 for bunglow and 0 for 2 story