A land developer wanted a model to estimate the selling pric

A land developer wanted a model to estimate the selling price of beach lots. To do so she recorded for each of 20 beach lots recently sold:

Y = Sale price of the beach lot in $10,000 units

X1 = Area of the lot (in hundreds of square feet)

X2 = elevation of the lot (in feet above sea level)

X3 = Slope of the lot toward the ocean (in degrees)

A statistical regression program generated the following output:

Multiple R:          0.8854

R Squared:          0.7838

Std. Error of Est.: 0.6075

Analysis of variance

Source

D of F

Sum of Squares

Mean Square

F-Ratio

Regression

3

21.409

7.136

19.345

Error

16

5.903

0.369

Individual Analysis of Variables

Variable

Coefficient

Std. Error

t-Value

Constant

-2.491

Area

0.099

0.058

1.713

Elevation

0.029

0.006

4.830

Slope

0.086

0.031

2.800

b) what percentage of the variation in selling price is explained by the three predictor variables?

Source	D of F	Sum of Squares	Mean Square	F-Ratio
Regression	3	21.409	7.136	19.345
Error	16	5.903	0.369

Solution

b) what percentage of the variation in selling price is explained by the three predictor variables?

  

A statistical regression program generated the following output:

Multiple R:          0.8854

R Squared:          0.7838

Std. Error of Est.: 0.6075

R²   = 0.7838     =   78.38%

percentage of the variation in selling price is explained by the three predictor variables =78.38%