In this project, you will collect data from real world toconstruct a multiple regression model. The resulting model will beused for a prediction purpose. For example, suppose you areinterested in “sales price of houses”. In a multiple regressionmodel, this is called a “response variable”. There are manyimportant factors that affect the prices of houses.

Those factors include size (square feet), number of bedrooms,number of baths, age of the house, distance to a major grocerystore. The factors (or variables) which are used for a multipleregression model are called “explanatory variables” (or“independent variables”). Good choice of explanatory variables isone of the most important steps to construct a good multipleregression model. www.zillow.com, One of the most recognizedrealtor website in United States, provides predicted prices(“zestimate”) of houses. Now the goal of the project is toconstruct your own prediction model of house prices. The first stepof the project is to decide which explanatory variables you willuse. In this project, please find at least four explanatoryvariables.

Next step is data collection. You are required to collect atleast 100 observations (samples). Otherwise, you will not get fullcredits. Each observation must include sales value and all thevalues of explanatory variables of your choice. For example, ifyour explanatory variables are size, number of beds, number ofbaths, and age of houses, then the data set must be of thefollowing form