Question

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)

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. Conduct a test of significance for the slope, at a significance level of  =.05.
   1. Set up a two-sided test of hypothesis for.

2. At a significance level of .05, what is the critical t-value for the two-sided test? (hint: determine the degrees of freedom for a linear regression)

3. The test statistic value for from the Excel output above is?

4. Based on your answers in (ii) and (iii) determine whether we should accept of reject the null hypothesis H_0.

2. What conclusions can you draw about the significance of from your results? Is square feet area significant in determining Home Price? Number of baths?

3. Use the 95% confidence interval for   to determine by how much the price of a home can increase if square feet area increases by 1 unit?

Answer 1

The price of a home can increase $0.04 to $ 0.09 if square feet area increases by 1 unit when no. of bath rooms is kept fix.