Abstract
With the development of economy and the improvement of people's living standards, many people will try to buy houses. But when it comes to buying a house, people will also pay attention to some objective factors such as the size of the house and supporting facilities. This paper uses the statistical analysis software SPSS linear regression analysis, factor analysis, comparative analysis and other methods to analyze the impact of objective factors on house prices, through data analysis, the fitting degree also reached about 0.88. In the experimental results, it is found that taxi distance, market distance, hospital distance, carpet area, built up area, parking type, city type, rainfall have a significant impact on house prices. Because in real life, These objective factors will be considered when people choose to buy a house.
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