Abstract: Frying food is not only pleasant to taste buds, but also faced with the optimal choice of oil type and quality and safety issues. Many scholars have studied the choice of oil type and the frying time. From the perspective of statistics, this paper summarizes the research progress of common statistical data analysis methods in the analysis of frying oil’s physicochemical parameters. First, with table analysis, data of repeated experiments are put into the table in the form of mean value plus minus standard deviation in most research cases, and the three common analyzed physicochemical parameters are acid value, fatty acid and total polar compounds. Second, with visualization methods of straight bar charts, line charts and scatter plots, the straight bar charts are mainly used to show the content of physicochemical parameters under different frying oil, frying time, frying temperature or power levels of heating; the line charts are mainly used to analyze the changes of physicochemical parameters with frying time, frying temperature, frying oil or frying load; the scatter plots are mainly used to analyze the influence of frying time, frying times or oil density on physicochemical parameters, as well as the relationship between physicochemical parameters or the distribution of physicochemical parameters in different waste oil samples. Third, with fitting methods of linear fittings and nonlinear fittings, the linear fittings are mainly used to analyze the linear relationships of physicochemical parameters with frying time, frying times or dielectric constants, as well as the linear relationships between physicochemical parameters and near infrared spectrum, and to analyze the consistency between the measured values of physicochemical parameters and the predicted values of other models; The nonlinear fittings mainly involve the methods of polynomial fitting, exponential function fitting and logistic regression and they are used to analyze the complex relationships between some physicochemical parameters and frying time, and to classify oil according to physicochemical parameters. Fourth, about the correlation analysis of physicochemical parameters, most of the literatures are carried out by calculating the Pearson correlation coefficients between physicochemical parameters, and a small number of literatures use the linear or nonlinear fitting methods between physicochemical parameters to analyze the correlation. Fifth, Analysis of variance is mainly used to study the changes of physicochemical parameters under different frying factors. Sixth, the principal component analysis is mainly used to analyze the importance of each physicochemical parameter to the quality control of frying oil, and so on. Through the above description of the progress of the statistical analysis methods for the physicochemical parameters of frying oil, it provides the researchers with some ideas for the selection of research methods and means.