Multiple Regression Analysis Case #28, Housing Pri

1076 Words5 Pages
Victoria Bilanin Multiple Regression Analysis Professor Sharma, Daoki 12 December 2011 Case #28, Housing Prices II Executive Summary In this report I will be using a multiple regression analysis approach to predict what the appropriate selling price is of my home in Eastville, Oregon. This approach is a statistical analysis that will explain the correlation between several selling features (independent variable) along with the selling price of a home (dependent variable). This type of approach is valuable as it will provide a systematic type approach that will be able to be duplicated and used to help others who are trying to sell there homes and are unsure of what the selling price should be. Introduction: I currently own a home in Eastville, Oregon. I am like many homeowners in these hard times and am looking to find any way not only to save, but to also find additional income. I have been thinking of selling my home for a while, but simply do not want to pay the Realtor commissions, as my home has already lost a little value with the ever declining economy. So I have decided that I would conduct my own systematic approach to help me determine what the value of my home is by using commonly sought after features of the homes. This has really helped me to determine what the appropriate asking price was for my home and this can be used by anyone who is thinking of selling their home. Methods and Analysis The main question of interest is how we determine the selling price of a house. By using Multiple Regression analysis for this research we can determine the selling price of a house using one dependent variable on the basis of other independent variables. We start by stating our Null Hypothesis Ho and the Alternative Hypothesis Ha. Ho:B1 = B2 = …. = Bj = 0, this means that none of the independent variables are significantly related to

More about Multiple Regression Analysis Case #28, Housing Pri

Open Document