Modelo Naive
\[
\operatorname{PRICE} = \alpha + \beta_{1}(\operatorname{HEIGHT}) + \beta_{2}(\operatorname{WIDTH}) + \beta_{3}(\operatorname{SIGNED}) + \beta_{4}(\operatorname{HOUSE}) + \epsilon
\]
|
Observations
|
430
|
|
Dependent variable
|
PRICE
|
|
Type
|
OLS linear regression
|
|
F(4,425)
|
24.39
|
|
R²
|
0.19
|
|
Adj. R²
|
0.18
|
|
|
Est.
|
S.E.
|
t val.
|
p
|
|
(Intercept)
|
-5.52
|
1.09
|
-5.05
|
0.00
|
|
HEIGHT
|
0.09
|
0.02
|
4.18
|
0.00
|
|
WIDTH
|
0.11
|
0.02
|
5.29
|
0.00
|
|
SIGNED
|
2.29
|
0.50
|
4.56
|
0.00
|
|
HOUSE
|
0.39
|
0.33
|
1.19
|
0.24
|
|
Standard errors: OLS
|
\[
\operatorname{PRICE} = -5.52 + 0.09(\operatorname{HEIGHT}) + 0.11(\operatorname{WIDTH}) + 2.29(\operatorname{SIGNED}) + 0.39(\operatorname{HOUSE}) + \epsilon
\]