Research on the Influencing Factors of Automobile Price Based on Multiple Linear Regression Model

With the rapid development of the economy and technology, the living standard of the people has been continuously improved. The consumption level of residents has also been increasing. Because automobiles have generally become the major means of transportation for modern people, the price of cars has steadily caught people's attention. Until now, most individuals are unaware of the relevant parameters and indicators within the car. As a result, many consumers will be confused when selecting an automobile. This paper aims to address any issues potential car buyers could have. The research uses SPSS software to establish a multiple linear regression model of the factors affecting car prices based on the data set on Kaggle. The research methods of this paper are as follows: to test the significance of the results of the model, including the estimation and test of the regression parameters and equation; Diagnosis and treatment of multicollinearity and heteroscedasticity of the model results, and make certain statistical analysis; Eliminate the inconspicuous factors and factors that don’t conform to economic significance. The research indicates that engine location, curb weight, number of cylinders, and drive wheels are examined as the significant factors that affect the car price. The research results of this paper provide a reference basis for consumers when purchasing cars, and help consumers to purchase the desired car products.