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

DOI

10.2991/asshm-13.2013.30How to use a DOI?

Keywords

parameter estimation, hypothesis testing, multiple linear regression, principal component regression, agricultural output

Abstract

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2013 International Conference on Advances in Social Science, Humanities, and Management
PB  - Atlantis Press
SP  - 165
EP  - 170
SN  - 1951-6851
UR  - https://doi.org/10.2991/asshm-13.2013.30
DO  - 10.2991/asshm-13.2013.30
ID  - Dong2013/12
ER  -