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 = ß+ Bedroom + yHouse Size + ¿Lot Size Predictor Coef SE Coef T P Constant 37718 2.66 ** Bedrooms 2306 0.33 74.3 * -4.36 House Size Lot Size S= 25023 Source Regression Residual Error Total R-Sq=56.0% 99 14177 6994 52.98 17.02 DF SS MS 3 76501718347 25500572782 96 60109046053 626135896 99 R-Sq (adj)=54.6% 0.742 0.164 -0.26 0.798 F *** P d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term "R-sq" and comment on its value.
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 = ß+ Bedroom + yHouse Size + ¿Lot Size Predictor Coef SE Coef T P Constant 37718 2.66 ** Bedrooms 2306 0.33 74.3 * -4.36 House Size Lot Size S= 25023 Source Regression Residual Error Total R-Sq=56.0% 99 14177 6994 52.98 17.02 DF SS MS 3 76501718347 25500572782 96 60109046053 626135896 99 R-Sq (adj)=54.6% 0.742 0.164 -0.26 0.798 F *** P d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term "R-sq" and comment on its value.
Chapter4: Linear Functions
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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 = ß + Bedroom + yHouse Size + Lot Size
Predictor
Coef
SE Coef
T
P
37718
**
2.66
0.33
2306
74.3
*
-4.36
Constant
Bedrooms
House Size
Lot Size
S= 25023
Source
Regression
Residual
Error
Total
DF
3
22
96
99
R-Sq=56.0%
14177
6994
52.98
17.02
0.742
0.164
-0.26 0.798
R-Sq (adj)=54.6%
SS
MS
F
***
76501718347 25500572782
60109046053 626135896
P
****
d) Is y significantly different from -0.5?
e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses.
f) Give an interpretation to the term "R-sq" and comment on its value.
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