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
1608	2	1	101200
1730	3	2	106800
1793	3	6	137200
2024	3	6	149400
2160	3	7	162000
2189	3	9	175700
2303	3	10	209600
2425	4	12	250000
2575	4	12	259300

Copy Data

Step 2 of 2 :  

Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.01 level of significance. If the relationship is statistically significant, identify the multiple regression equation that best fits the data, rounding the answers to three decimal places. Otherwise, indicate that there is not enough evidence to show that the relationship is statistically significant.

Answer 1

The statistical software output for this problem is:

Hence,

The multiple regression will be:

Selling price = -78477.284 + 80.419 sqft + 12753.987 Bedrooms + 5968.339 Age