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Seven factors which influence China’s agricultural output are selected to analyze the relationship between agricultural output and the factors. Parameter estimation, hypothesis testing, and regression analysis are applied to build up the model. Multiple linear regression and principal component regression are used to model the data. Based on the data collected from National Bureau of Statistics of China, three principal components, namely basic element component, balance component, and utility component are derived. Reasonable explanations that are consistent with China’s reality are made from the principal components and factors to the contribution of the agricultural output. Finally, several reasonable suggestions are given according to the analysis.

Regression Analysis on Chinese Agricultural Output and Its Influencing Factors Based on R