Question

You are a new hire at Laurel Woods Real Estate, which specializes in selling foreclosed homes via public auction. Your boss has asked you to use the following data (mortgage balance, monthly payments, payments made before default, and final auction price) on a random sample of recent sales in order to estimate what the actual auction price will be. Add a new variable that describes the potential interaction between the loan amount and the number of payments made.

Loan			Monthly Payments			Payments Made		Auction Price
$	85,605		$	1,069.80		1		$	52,775
	110,284			993.88		34			46,450
	109,719			741.28		4			46,150
	120,811			977.19		12			16,600
	97,600			836.53		19			40,700
	104,400			983.27		19			63,100
	113,800			1,075.54		17			72,600
	116,400			1,087.16		35			72,300
	100,000			900.01		33			58,100
	92,800			683.11		36			37,100
	105,200			915.24		34			52,600
	105,900			905.67		38			51,900
	94,700			810.70		25			43,200
	105,600			891.33		20			52,600
	104,100			864.38		7			42,700
	85,700			1,074.73		30			22,200
	113,600			871.61		24			77,000
	119,400			1,021.23		58			69,000
	90,600			836.46		3			35,600
	104,500			1,056.37		22			63,000

Determine the regression equation. (Round your answers to 3 decimal places. Negative amounts should be indicated by a minus sign.)

	Auction Price =    +    Loan +    Monthly Payment + Payments Made +    x1x3

Complete the following table. (Round your answers to 3 decimal places. Leave no cells blank - be certain to enter "0" wherever required. Negative amounts should be indicated by a minus sign.)

	Predictor Coefficient SE Coefficient t p-value Constant Loan Monthly Payment Payments Made (Loan)(Payments Made

Compute the t-value corresponding to the interaction term. (Round your answer to 2 decimal places. Negative amount should be indicated by a minus sign.)

	t-value:

  

Answer 1

Output using excel:

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.583722
R Square	0.340731
Adjusted R Square	0.164926
Standard Error	14812.95
Observations	20
ANOVA
	df	SS	MS	F	Significance F
Regression	4	1.7E+09	4.25E+08	1.938118	0.156267
Residual	15	3.29E+09	2.19E+08
Total	19	4.99E+09
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	43625.222	67091.63	0.650233	0.525376	-99377.2	186627.6
Loan	-0.09752	0.54683	-0.17834	0.860842	-1.26306	1.068018
Monthly Payments	13.98163	31.62889	0.442053	0.664758	-53.4337	81.39702
Payments Made	-2917.241	2178.119	-1.33934	0.200402	-7559.79	1725.31
x1x3	0.029311	0.020401	1.436787	0.171309	-0.01417	0.072794

Regression equation:

Auction Price = 43625.222 + (-0.098)Loan + (13.982) Monthly Payments + (-2917.241)Payments Made + (0.029) x1x3

	Coefficients	Standard Error	t Stat	P-value
Intercept	43625.222	67091.626	0.650	0.525
Loan	-0.098	0.547	-0.178	0.861
Monthly Payments	13.982	31.629	0.442	0.665
Payments Made	-2917.241	2178.119	-1.339	0.200
x1x3	0.029	0.020	1.437	0.171

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t-value corresponding to the interaction term = 1.44