Question

A national homebuilder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. Click the icon to view the house sales data. a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Sales Price = + (1) • Lot Cost + ( )• Townhouse (Type integers or decimals rounded to two decimal places as needed.) b. What is the predicted sales price for either a single-family home or a townhouse with a lot cost of $29,400? 1. b.1 The predicted sales price for a single-family home is $ (Round to the nearest cent as needed.) . b.2 The predicted price for a townhouse is $ (Round to the nearest cent as needed.)

Type   Sales_Price   Lot_Cost
Townhouse   114740   21700
Single Family   138530   26550
Townhouse   149905   25550
Single Family   172000   26200
Townhouse   183916   46025
Townhouse   189390   28000
Single Family   191120   36000
Townhouse   198898   46025
Townhouse   205076   46025
Single Family   207821   40299
Single Family   216205   37500
Townhouse   252800   74400
Single Family   257000   44198
Single Family   270000   44344
Single Family   270500   42099
Single Family   273105   46000
Single Family   279720   45650
Single Family   296990   58000
Single Family   303500   60000
Single Family   309487   46850
Single Family   314898   41768
Single Family   321602   83300
Single Family   326412   63523
Single Family   339374   71449
Single Family   339380   50150
Single Family   340065   55850
Single Family   356117   57219
Single Family   361949   51591
Single Family   434426   58422
Single Family   494820   85122

Answer 1

using excel>data >data analysis>Regression

we have

Regression Analysis
Regression Statistics
Multiple R	0.855998278
R Square	0.732733052
Adjusted R Square	0.7129355
Standard Error	46814.52571
Observations	30
ANOVA
	df	SS	MS	F	Significance F
Regression	2	1.62228E+11	81113950015	37.01129622	1.83553E-08
Residual	27	59173195060	2191599817
Total	29	2.21401E+11
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	108726.1148	30018.66895	3.621949893	0.001192186	47132.89378	170319.3358
Lot_Cost	3.680896898	0.557046907	6.607876015	4.33677E-07	2.537931055	4.823862742
Type	-75063.40907	20940.85038	-3.584544454	0.001313466	-118030.4849	-32096.33323

a ) the multiple regression equation is

Sales Price = 108726.12+0.68*Lot Cost -7506.41 Townhouse

b 1 ) the predicted price for single family home is = 108726.12+0.68*29400 -7506.41*0 =128718.12 ~$128718

b2 )the predicted price for Townhouse is = 108726.12+0.68*29400 -7506.41*1 =121211.71 ~$121212