Abstract
This article aims to identify those factors that have an impact in housing prices. The sample of the study is 15 variables, including 19554 pieces of data. Among the 15 variables, there are both factors of the house itself and some external influencing factors. The method of Multiple Linear Regression is used to analyze the significant factors with the housing prices of Kansas City. Based on these 15 variables it does correlate with house prices. The 19554 data substituted into Multiple Linear Regression Model. The result shows that grade, latitude, years of built, waterfront, view, square of basement, square of above, zip code, bathrooms and condition have a significant linear relationship with prices, while the id, date, bedrooms, square of lot, floors and year of renovating fail the significance test. In totally, the volatility of housing prices in Kansas City can be considered by the extent to which these factors affect them.
Published Version
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