Question

HW # 5

Linear Regression:

Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel out put below (Note: First enter the data in the next page in an Excel spreadsheet)

Home Sale Price: The table below provides the Excel output of a regression analysis of the relationship between Home sale price(Y) measured in thousand dollars and Square feet area (x):   

SUMMARY OUTPUT		Dependent:	Home Price	($1000)
Regression Statistics
Multiple R	0.691
R Square	0.478
Adjusted R Square	0.465
Standard Error	27.21
Observations	80
ANOVA
	df	SS	MS	F	Significance F
Regression	2	52378.32252	26189.16126	35.36552756	1.27417E-11
Residual	77	57020.65136	740.5279397
Total	79	109398.9739
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	11.581	29.82	0.388	0.698755345	-47.80910537	70.98276434
Size(Sqft)	0.069	0.014	5.56	3.67568E-07	0.044314403	0.093711307
Bathrooms	17.807	7.33	2.42	0.017548601	3.198869475	32.41601103

1. Interpret the meaning of the coefficient value for. How are square feet area and the price of a home related?

Answer 1

the regression equation is :-

home price = 11.581 + 0.069 size + 17.807 bathrooms

a). the meaning of the coefficient value for. How are square feet area and the price of a home related is:-

For each 1 unit(squarefeet) increase in home size , the home price increases by 0.069 units(in $ 1000), keeping number of bathrooms constant.

in other words, for each 1 squareffet increase in home size, home price increases by 69 dollars, keeping number of bathrooms fixed.

[ 0.069 thousand dollars = $ (0.069*1000) = $ 69 ]

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