2013•Anhui nongye kexueRequires access

Statistical Analysis of the Factors Influencing Shaanxi Farmers Net Income Per Capita

Zhao Chun-xian

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Abstract

The heart of the problem ofagriculture,rural areas and farmersis the increase of farmers' income,only to increase income can fundamentally improve the farmer's quality of life. According to data of the farmers' income in Shanxi Province from 2000 to 2011,selecting 6 important influencing factors,the statistical model was established by principal component regression analysis,avoiding the possible multicollinearity between variables. By using R software,the contribution rate of farmers income growth was obtained. According to the analysis results,corresponding suggestions were put forward.

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What this paper is about

The heart of the problem ofagriculture,rural areas and farmersis the increase of farmers' income,only to increase income can fundamentally improve the farmer's quality of life. According to data of the farmers' income in Shanxi Province from 2000 to 2011,selecting 6 important influencing factors,the statistical model was established by principal component regression analysis,avoiding the possible multicollinearity between variables. By using R software,the contribution rate of farmers income growth was obtained. According to the analysis results,corresponding suggestions were put forward.

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Available abstract

The heart of the problem ofagriculture,rural areas and farmersis the increase of farmers' income,only to increase income can fundamentally improve the farmer's quality of life. According to data of the farmers' income in Shanxi Province from 2000 to 2011,selecting 6 important influencing factors,the statistical model was established by principal component regression analysis,avoiding the possible multicollinearity between variables. By using R software,the contribution rate of farmers income growth was obtained. According to the analysis results,corresponding suggestions were put forward.

Key concepts: Multicollinearity, Per capita income, Net income, Principal component analysis, Per capita, Statistical software, Regression analysis, Agricultural economics

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