Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef т P 37718 14177 2.66 ** Constant Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq (adj) =54.6% Source DF SS MS F P Regression 3 76501718347 25500572782 *** **** Residual 96 60109046053 626135896

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 17HP
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Bluereef real estate agent wants to form a relationship between the prices of houses, how many
bedrooms, House size in sq ft and Lot Size in sq ft.
The data pertaining to 100 houses were processed using MINITAB and the following is an extract
of the output obtained:
The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size
Predictor
Coef
SE Coef
т
P
37718
14177
2.66
**
Constant
Bedrooms
2306
6994
0.33
0.742
House Size
74.3
52.98
0.164
Lot Size
-4.36
17.02
-0.26
0.798
S= 25023
R-Sq=56.0%
R-Sq (adj) =54.6%
Source
DF
SS
MS
F
P
Regression
3
76501718347 25500572782
***
****
Residual
96
60109046053
626135896
Error
Total
99
f) Give an interpretation to the term "R-sq" and comment on its value.
Transcribed Image Text:Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef т P 37718 14177 2.66 ** Constant Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq (adj) =54.6% Source DF SS MS F P Regression 3 76501718347 25500572782 *** **** Residual 96 60109046053 626135896 Error Total 99 f) Give an interpretation to the term "R-sq" and comment on its value.
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