Proceedings of the 2013 International Conference on Advances in Social Science, Humanities, and Management

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

Authors
Meichen Dong, Yingying Zhang
Corresponding Author
Meichen Dong
Available Online December 2013.
DOI
https://doi.org/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.
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Proceedings
2013 International Conference on Advances in Social Science, Humanities, and Management (ASSHM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2013
ISBN
978-90-78677-93-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/asshm-13.2013.30How to use a DOI?
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
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  -