Question

The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x1) is the square footage, the second independent variable (x2) is the number of bedrooms, and the third independent variable (x3) is the age of the house. Effects on Selling Price of Houses Square Feet Number of Bedrooms Age Selling Price 2460 3 15 296700 2261 4 7 101700 1748 3 7 201000 2743 4 6 207400 1702 5 4 129300 1756 4 2 147600 1728 3 3 184600 1384 5 12 163400 1551 2 15 160900 Step 1 of 2: Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places

Answer 1

square Feet	No of Bed room	Age	Selling Price
2460	3	15	296700
2261	4	7	101700
1748	3	7	201000
2743	4	6	207400
1702	5	4	129300
1756	4	2	147600
1728	3	3	184600
1384	5	12	163400
1551	2	15	160900

#we fit multiple linear regression in Excell

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.656631
R Square	0.431165
Adjusted R Square	0.089864
Standard Error	53479.83
Observations	9
ANOVA
	df	SS	MS	F	p-value
Regression	3	1.08E+10	3.61E+09	1.263297	0.381163858
Residual	5	1.43E+10	2.86E+09
Total	8	2.51E+10
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	98679.04	126846.9	0.777938	0.471794	-227391.3554	424749.4	-227391	424749.4
square Feet	51.04441	41.69754	1.224159	0.275422	-56.14252356	158.2313	-56.1425	158.2313

Hence,

p - Value = 0.3815

Since the relationship is not significant, do not put any values in the equation. Just click the check box and it will be correct.