Estimation of House Selling Price by Multiple Regression Analysis Using SAS Software

Abstract

Regression analysis is one of the most widely used statistical techniques. Today, regression analysis is applied in the social sciences, medical research, economics, agriculture, biology, meteorology, marketing, retail, insurance and many other areas of academic and applied science. It is not only suited to suggesting decisions as to whether or not a relationship between two variables exists. It goes beyond this decision making and provides a different type of precise statement. Regression analysis specifies a functional form for the relationship between the variables under study that allows one to estimate the degree of change in the dependent variable that goes hand in hand with changes in the independent variable. At the same time, regression analysis allows one to make statements about how certain one can be about the predicted change in Y that is associated with the observed change in X.

The main objective of the present study is to investigate factors that contribute significantly to estimate the selling price of a house in a locality. The dependent variable is Average house selling price, the multiple regression analysis applied for exploring the factors affecting the house selling price. The power of SAS in analysing data patterns and developing such models is also demonstrated, appropriateand relevant portions of SAS code are included where possible.