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 (x1x1) is the square footage, the second independent variable (x2x2) is the number of bedrooms, and the third independent variable (x3x3) is the age of the house.

Effects on Selling Price of Houses

Square Feet	Number of Bedrooms	Age	Selling Price
28952895	55	1515	238300238300
25932593	55	1212	220500220500
23572357	33	88	205900205900
19711971	33	77	193200193200
18231823	33	66	183400183400
17121712	33	55	166900166900
16561656	22	44	159300159300
15441544	22	22	129600129600
10901090	22	11	101600101600

Copy Data

Step 1 of 2 :  

Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places.

What do you need to put in Input x and Input y range cells? I am stuck here

Answer 1

y = Selling price

x = Square Feet , Number of Bedrooms , Age

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-10148021318.523	20974633096.368	-0.484	0.649	-64065032165.183	43768989528.138	-64065032165.183	43768989528.138
Square Feet	7511.512	1401.690	5.359	0.003	3908.353	11114.670	3908.353	11114.670
Number of Bedrooms	1570355387.552	911722020.911	1.722	0.146	-773300678.551	3914011453.655	-773300678.551	3914011453.655
Age	-38470536.621	15424874.130	-2.494	0.055	-78121437.876	1180364.633	-78121437.876	1180364.633

ANOVA
	df	SS	MS	F	Significance F
Regression	3	14657438840317300000000.00	4885812946772450000000.00	51.46	0.0004
Residual	5	474751424017788000000.00	94950284803557500000.00
Total	8	15132190264335100000000.00

As u can see above in bold

p value for model = 0.0004

THANKS

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