A real estate agent wanted to find the relationship between sale price of houses and the size of the house. She collected data on two variables recorded in the following table for 15 houses in Seattle. The two variables are

PRICE= Sale price of houses in thousands of dollars

SIZE= Area of the entire house in square feet.

Price 455 278 463 327 505 264 445 346 487 289 434 411 223 323 488 Size 2500 2250 2900 1800 3200 2400 2700 2050 2850 2400 2600 2300 1700 2300 2980 

1.Using MICROSOFT EXCEL- run the above regression and copy the output into a word document with the least square regression line. Write down the least square regression line from that specific output. USE THE NAME OF VARIABLES WHEN YOU WRITE THE EQUATION.

2.Interpret the slope and constant term with proper UNITS.

3.Comment on the explanatory power of the regression model from the required output.

Now to increase the explanatory power of the model the real estate agent decides to look at the age of the house and the garden size. For the 15 houses in our sample the new variables are

AGE= Age of the house in years, since it was built

GARDEN= Area of the garden in acres.

Age 8 12 5 9 4 28 9 13 7 16 5 8 19 17 9 Garden 1.4 0.9 1.8 0.7 2.6 1.2 2.1 1.1 2.8 1.6 3.2 1.7 0.5 2.7 0.5 2.7 3.4 

4.Once these two new variables are added- run the new regression using MICROSOFT EXCEL. write down the new least square regression line. Write down the new least square regression line from that specific output. USE THE NAME OF VARIABLES WHEN YOU WRITE THE EQUATION.

5.Interpret the coefficients with all the independent variables with proper UNITS.

6.Comment on the explanatory power of the regression model from the required output. Copy the output and paste word document.

7.Compare the two regression models that you have found using the appropriate parameter. Which is better and why? Give proper reasoning.

If you were to add a DUMMY VARIABLE in this regression model what would be an appropriate one? Why? Give sound logical reasoning.