Published Paper Details:

Real estate is the least transparent industry in our ecosystem. Housing prices keep changing day in and day out and sometimes are hyped rather than being based on valuation. Predicting housing prices with real factors is the main crux of our research project. Here we aim to make our evaluations based on every basic parameter that is considered while determining the price. In this paper, we performed multiple linear regression for estimating house price based on area in square feet and number of bed rooms. Regression is a measure of the relation between the mean value of one variable and corresponding values of other variables. In statistical modelling, regression analysis is a set of statistical processes for estimating the relationships among variables. The multiple linear regression explains the relationship between one continuous dependent variable (y) and two or more independent variables (x1, x2, x3...etc). Here we implemented through three modules: Data entry module, is used to provide the needed data to the project. The Analysis module is used to analyse and predict the house prices, based on the customer needs. The Front-end module is used to create the needed GUI screens for the project.