# Finding The Price Of A Home Using Regression

3194 words - 13 pages

James HollidayGM53312/13/2008Executive SummaryThe analysis in this paper was utilized to find an equation that predicts the selling price of a house. The null hypothesis states that there is no clear and definitive relationship between the selling price of a house and the characteristics of the house. The alternate hypothesis states that there is definitely a relationship between the selling price of a house and the characteristics. A 95% confidence level and a confidence interval estimate of a predicted value of the selling price were used. The MegaStat output of a Regression Analysis of the data was used as the foundation to calculate the multiple regression equation. The point prediction of the selling price of a house corresponding to the variations of values of the independent variables is: Y = -12.5988 + 0.0383(X1) + 4.3573(X2) -14.5371(X3) + 16.0610(X4) + 11.3576(X5) - 1.2168(X6) which is given on the MegaStat output later in this paper. The MegaStat output shows that there is very strong evidence that these variables are definitely related to the selling price and indeed very important in this model. The results from the data show that the alternate hypothesis should be accepted.Introduction and PurposeThe purpose of this analysis is to find the equation that predicts the selling price of a house. While the focus of this paper is predicting the selling price of a house in Eastville, Oregon, the method discussed in this paper would also be easily utilized for data from other areas or countries. One major problem in measuring housing price growth results from the inconsistencies of transactions. To be meaningful, price data should be based on transaction prices rather than valuations.One of the most important things you need to know when selling a house is the maximum you should pay for a property so that you can ensure making a good profit. The key to determining your maximum cash offer is to know how to predict the value without relying on Realtors or any other third parties. There are many different house price resources that can be obtained to get the latest information on property prices and the patterns and trends of growth of the housing market, but this also makes it almost impossible to know which one you can trust to be accurate. To further enhance this information, the type of property and any adjustments needed should be included and at this time the information is not obtainable because that kind of an index does not exist. When it comes to the effects of short term house price inflation, property price volatility, and the recent housing market and mortgage crisis, the house price index is a very complex and extensive equation. There are many problems with predicting house prices due to the nature of the market where no sale is the same and a house that is identical to another can sell for a different price for any number of reasons including location, whether extra work had been done on the property, or due to the negotiations...

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