Develop a regression model for predicting the asking price of a house.
Suppose that you would be selling your house and you are trying to develop a model to predict the eventual sale price of your home. You are interested in getting as many offers as possible so you do not want to set the asking price of the house too high because that would result in fewer people considering the property. Then again if the asking price is too low, you might be tempted to sell the property at too low a price and not realize an appropriate profit. You have available some old data (about ten years old) which you feel is the best you can get in the time frame in which you are working. You feel that by about doubling the old prices you would get values that are appropriate for current home sales.
Choose a random sample of 50 homes from the enclosed 90 cases. Double the asking price and selling price and use this data to develop three predictive models:
Build up a model for predicting the asking price of a house.