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The Second-Hand House Price Prediction Using Multiple Linear Regression Model
- 1 Binghamton University
* Author to whom correspondence should be addressed.
Abstract
Analyze the influencing factors of second-hand housing and build the relevant model using the data on second-hand housing prices in 2017-2018. The R-code analysis is used to construct a prediction model of house prices, and the main factors affecting their changes are obtained. According to the significance test, the model meets the expectation and is feasible. Finally, it is concluded that the most noticeable impact on housing prices is room distribution and ladder ratio, and the least obvious is trade time.
Keywords
second-hand house price forecast, multiple linear regression model, regression analysis
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Cite this article
Jin,Y. (2023). The Second-Hand House Price Prediction Using Multiple Linear Regression Model. Advances in Economics, Management and Political Sciences,15,337-345.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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