PART 2 PURPOSE: The purpose of this assignment is to provide the students with the skill to estimate demand functions and its application in the real world. REQUIREMENT: A company wants to develop a model to determine a suggested listing price for houses based on the size of the house and the age of the house. She selects a sample of houses that have sold recently in a particular area, and she records the selling price, the square footage of the house, the age of the house and also the condition (good, excellent or mint) of each house as shown in Table 1: Selling Price Square Footage Age Excellent house* Mint House* Condition ($) (feet) (Years) 95,000 1,926 30 Good 119,000 2,069 40 Excellent 124,800 1,720 30 Excellent 135,000 1,396 15 Good 142,800 1,706 32 Mint 145,000 1,847 38 Mint 159,000 1,950 27 Mint 165,000 2,323 30 Excellent 182,000 2,285 26 Mint 183,000 3,752 35 Good 200,000 2,300 35 Good 211,000 2,525 17 Good 215,000 3,800 40 Excellent 219,000 1,740 12 Mint Note: *1 - if house is in excellent/mint condition and 0 - otherwise You are required to do the following: 1. Initially the company plans and believes that a better model can be developed if all the variables are being used in the regression equation. a. Write the estimated regression equation. (5) b. Interpret economically the estimated intercept (a) and slope (b) coefficient. (2.5) C. Test the hypothesis (at 0.05 level) that there is no relationship (ie., P = 0) between the variables. (2.5) d. Calculate the coefficient of determination. (2.5) e. Perform an analysis of variance on the regression, including an F-test of the overall significance of the results (at 0.05 level). (2.5)