Research on Prediction and Analysis of Real Estate Market Based on the Multiple Linear Regression Model

Since the housing reform in the 1990s, China's real estate market has expanded and developed rapidly. It has quickly become the pillar of China's national economy and made a great contribution to China's economic growth. However, China's real estate market started late and its development is not perfect, and house prices show obvious volatility. Accurate prediction of house prices is conducive to the government issuing appropriate regulatory policies, helping investors formulate correct investment strategies, and guiding the healthy and long-term development of the real estate market. Based on the statistical data of the real estate market, this study analyzes the influencing factors of the real estate price, establishes a multiple linear regression model, uses the least square method to solve the unknown parameters of the model, and finally constructs a house price prediction model to predict and analyze the real estate market. The results show that the maximum error of the real estate price prediction model is no more than 8%. The above results show that the house price prediction model has high accuracy and can predict house prices accurately and efficiently.