基于多角度线性回归分析的第32届奥运会前十名国家成绩预测

Performance Forecast of the Top 10 Countries of the 32nd Olympic Games Based on Multi-Angle Linear Regression Analysis

本文主要探讨了奥运会奖牌榜的预测问题,主要通过建立线性回归(一元及多元)模型、使用SPSS和Excel等软件对历届奥运会奖牌榜进行多角度分析并得到最优预测模型。在模型一的建立中,本文使用时间序列法进行预测、建立回归模型。由于模型一中对于某些国家奖牌榜预测与实际出入较大,在模型二的建立中,本文综合考虑了GDP,人口数量,东道主效应等因素建立多元回归模型。综合模型一与模型二的求解结果,得到2020年东京奥运会奖牌榜前十名及其金牌数与奖牌数。

this paper mainly discusses the forecasting problem of Olympic medals list, mainly through the establishment of linear regression(one dollar and multiple elements) model, the use of SPSS and Excel and other software to carry out multi-angle analysis of successive Olympic medals list and get the best prediction model. In the establishment of model one, this paper uses time series method to predict and establish regression model. Due to the large difference between the forecast and the actual number of medals in some countries in model 1, in the establishment of model 2, this paper comprehensively considers the factors such as GDP, population, and host effect to establish a multiple regression model. The results of the comprehensive model 1 and model 2 solutions obtained the top ten medals in the 2020 Tokyo Olympic Games and the number of gold medals and medals.