Regression Analysis on Chinese Agricultural Output and Its Influencing Factors Based on R
Meichen Dong, Yingying Zhang
Available Online December 2013.
- https://doi.org/10.2991/asshm-13.2013.30How to use a DOI?
- parameter estimation, hypothesis testing, multiple linear regression, principal component regression, agricultural output
- 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. Rea-sonable 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Meichen Dong AU - Yingying Zhang PY - 2013/12 DA - 2013/12 TI - Regression Analysis on Chinese Agricultural Output and Its Influencing Factors Based on R BT - 2013 International Conference on Advances in Social Science, Humanities, and Management (ASSHM-13) PB - Atlantis Press SP - 165 EP - 170 SN - 1951-6851 UR - https://doi.org/10.2991/asshm-13.2013.30 DO - https://doi.org/10.2991/asshm-13.2013.30 ID - Dong2013/12 ER -