Column name	Description
Price ($1000s)	Price of the house (in $1000s)
Bath	Number of bathrooms
Area	Area of the house (in square feet)
Lot	House lot size (in acres)
Central_cooling	1 if the house has central cooling and 0 if not
Bed	Number of bedrooms
Heat_pump	1 if the house has a heat pump and 0 if not

Model 1

Regression Statistics
Multiple R	0.53
R Square	0.28
Adjusted R Square	0.28
Standard Error	191.66
Observations	98
ANOVA
	df	SS	MS	F	Significance F
Regression	1	1403819.33	1403819.33	38.22	1.5355E-08
Residual	96	3526382.81	36733.15
Total	97	4930202.14
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	244.62	54.55	4.48	2.02661E-05	136.34	352.90	136.34	352.90
lot	551.73	89.25	6.18	1.5355E-08	374.58	728.89	374.58	728.89

Model 2

Regression Statistics
Multiple R	0.78
R Square	0.61
Adjusted R Square	0.58
Standard Error	146.27
Observations	98
ANOVA
	df	SS	MS	F	Significance F
Regression	6	2983351.16	497225.2	23.24137	1.8125E-16
Residual	91	1946850.981	21393.97
Total	97	4930202.141
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-69.27	80.53	-0.86	0.391949	-229.24	90.69	-229.24	90.69
bath	46.77	24.03	1.95	0.054708	-0.96	94.51	-0.96	94.51
area	0.11	0.02	4.49	0.000021	0.06	0.15	0.06	0.15
lot	330.75	74.50	4.44	0.000025	182.76	478.74	182.76	478.74
Central_cooling	88.35	30.43	2.90	0.004624	27.92	148.79	27.92	148.79
bed	-12.40	26.13	-0.47	0.636116	-64.30	39.50	-64.30	39.50
Heat_pump	39.52	39.90	0.99	0.324538	-39.73	118.78	-39.73	118.78

Model 3

Regression Statistics
Multiple R	0.77
R Square	0.60
Adjusted R Square	0.58
Standard Error	145.67
Observations	98
ANOVA
	df	SS	MS	F	Significance F
Regression	4	2956746.708	739186.7	34.83451	9.34467E-18
Residual	93	1973455.433	21219.95
Total	97	4930202.141
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-86.52	58.61	-1.48	0.143233	-202.90	29.86	-202.90	29.86
bath	44.85	21.99	2.04	0.044235	1.18	88.51	1.18	88.51
area	0.10	0.02	4.42	0.000027	0.05	0.14	0.05	0.14
lot	331.29	74.18	4.47	0.000022	183.98	478.61	183.98	478.61
Central_cooling	90.98	30.16	3.02	0.003297	31.09	150.87	31.09	150.87

1. use the models you estimated in problem 1 through 3 (we'll call these "model 1", "model 2" and "model 3", respectively) to predict the value of a particular home. This home has two bathrooms, a total area of 2400 square feet, a lot size of 0.8 acres, central cooling, three bedrooms and a heat pump. What are the predicted prices for this house (in dollars) using model 1, model 2 and model 3? (i.e., predict three different prices using each model one at a time)

2. What is the 95% confidence interval for the average value of a house with the features given in this problem using model 3 (assume Distance Value = .0673)? (hint: you already calculated the center of this confidence interval using model 3 in part a)