A land developer wanted a model to estimate the selling price of beach lots. To
ID: 3434897 • Letter: A
Question
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
f) Find a 90% Confidence Interval for the regression parameter relating area to selling price using the model which also includes elevation and slope.
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
Explanation / Answer
90% CI for regression parameter of area is given by :
(beta^ - t16,0.05* (S.E (beta^)), beta^ + t16,0.05 * (S.E(beta^)))
= (0.099 - (1.713 * 0.058) , 0.099 + (1.713 * 0.058)) = (-0.000354, 0.1984) .
This is the requires CI for regression parameter relating
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