OPRE 6301

Module I - Descriptive Statistics

Assume that you will 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 since that would result in fewer people considering the property. On the other hand 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 approximately doubling the old prices you would get values that are appropriate for current home sales.

Assignment:

Pick 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:

1. Develop a model for predicting the asking price of a house;
2. Develop a model for predicting the selling price of a house;
3. Develop a model for predicting the difference in the asking price and selling price.

Show the steps and data for the steps you used in developing your model and discuss the "reasonableness" of the final models chosen. Specifically discuss their predictive ability as well as the inherent error in using them. Further comment on the final variables selected and whether or not they seem sensible based on your knowledge of real estate.

Price: $15.68

Solution: The downloadable solution consists of 9 pages, 668 words and 5 charts.
Deliverable: Word Document