Unveiling Factors Affecting Price of Second-hand Cars Using Multiple Linear Regression Models and Random Forest

With the development of global economy and evolution of consumer concepts, automobiles, as an important means of transportation and consumer product, have seen a continuous increase in market demand. In recent years, with the growing number of vehicles in use, the second-hand car market has gradually become an important part of the automotive circulation sector. This study investigates the factors influencing second-hand car pricing in the current market environment. By combining multiple linear regression and Random Forest analysis, the author examines the significance and impact of various factors on the final selling price of second-hand vehicles. The data were collected from Kaggle and supplemented by relevant academic literature, covering variables such as power, transmission, mileage, engine type, and fuel type. The author seeks to reveal the characteristics and trends of current second-hand car pricing, provide guidance for marketing strategies, offer a basis for relevant policy-making, and explore the long-term impact of second-hand car pricing on the entire consumer market and social-economic development. As the results, the vehicle's power has the greatest impact on the final transaction price, which is the pricing in the second-hand car market, and it is positively correlated.