5.2 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

$$\operatorname{PRICE} = -5.52 + 0.09(\operatorname{HEIGHT}) + 0.11(\operatorname{WIDTH}) + 2.29(\operatorname{SIGNED}) + 0.39(\operatorname{HOUSE}) + \epsilon$$