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
2848	4	6	242100
1270	4	7	113600
1825	4	8	281700
2235	5	5	199100
2072	4	2	307500
2197	4	14	278800
2184	4	5	275300
1764	4	7	107200
2276	4	14	103000

Step 1 of 2 :  

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

Step 2 of 2:

Determine if a statistically significant linear relationship exists between the independent and dependent variables at the 0.05 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:

From above output:

Step - 1: p - Value = 0.6051

Step - 2: Since p - value is greater than 0.05, we fail to reject Ho and hence, the equation is not significant. So,

There is not enough evidence to show that the relationship is statistically significant.