Good afternoon,

I am interested in the factors that affect the selling price of a house in the following problem question: Please help!

data from 27 houses is collected . For each house we record the"Selling price"and, except from the"Size"of the house, we also record the age of the house, the number of bedrooms and the number of bathrooms. The variable"Selling price"was recorded in SPSS in"thousands of euros"(i.e. 1 unit=?1000),the variable"Size of house"was recorded in square meters (i.e. 1 unit=1 square meter, m2), while the age of the house is in years.

SPSS the decimal point is denoted by the dot (.), (e.g. 21.892 is around 21).

I am given the following output from SPSS (attached)

Can you please assist in the following questions with explanations step by step?

(1) . What we conclude If we perfom an F test? Can you show the steps to understand?

(2)Based on the conclusion from part (1) we need to continue to test individually which of the variables are significant for the model? How we do that? Can you show the step to understand it?

(3)What is the final estimated model and how to interpret the coefficients?

(4)Is the final model better than the model which included only the Size of the House as an independent variable? how we explain it??

(5)What will be the selling price of a house that has size 300 square meters, it has 3 bedrooms, it is 10 years old and it has 2 bathrooms.

Model Summary Adjusted R Sto . Error of the Model R R Square Square Estimate* 894 . 799 . 763 103. 77668 ANOVA Model Sum of Squares DF Mean Square* F Sig . Regression 943063. 769 235765. 942 21.892 . 000 Residual 236931 . 194 22 10769. 600 Total 1 179 9 94. 963 26 Coefficients Standardized Unstandardized Coefficients Coefficients Model B Sto . Error Beta Sig. ( Constant ) 420. 254 231. 739 . 182 857 Size 304 . 060 665 5. 083 . 000 Bedrooms 236 3.657 .007 .065 949 Age -6.838 2.822 -. 346 -2. 652 . 015 Bathrooms 17. 106 35.589 . 052 . 481 . 636