(Solved): Please answer questions with fully explained procedures. Data is in the Excel spreadsheet ProjectDa ...

Please answer questions with fully explained procedures.

Data is in the Excel spreadsheet ProjectData.xlsx Descriptive Abstract: This dataset comprises 104 homes. Variable Descriptions: housenum: unique house number bedrooms: number of bedrooms bikescore: bike friendliness ( $0?100$ score, higher scores are better) garage_spaces: number of garage spaces $(0?4)$ distance: distance (in feet) to the nearest entry point to the rail trail network no_full_baths: number of full baths (includes shower or bathtub) no_half_baths: number of half paths (no shower or bathtub) price: Price at which the property closed in 2019 (in thousands of dollars) squarefeet: square footage of interior finished space (in thousands of sf) walkscore: walk friendliness (0-100 score, higher scores are better) zip: location (18892 = Funkytown) Answer the following questions based on the data. Clearly explain your procedure(s). First Step: Convert Zip: Location into a dummy variable with 1 for Funkytown and 0 otherwise. a) We wish to estimate the most that a homeowner should pay to add a bedroom that will add 500 square feet to the house. i. What is the dependent variable? ii. Use all the remaining variables (other than the house number) as independent variables and then run the regression. Using the results of your regression, what is the added value of an additional bedroom that adds 500 square feet to the house? b) Using the results of your regression, what is the extra value of having a house in Funkytown? c) Turn in the Excel spreadsheet with your regression results.