Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice
Objective To construct and compare the methods for correlation analysis of different elements in rice, including barium, vanadium, cadmium, lithium, aluminum, manganese, lead, thallium, antimony, copper, selenium, ehromium, mercury and arsenic. Methods Analyze the correlation among the fourteen elem...
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Format: | Article |
Language: | zho |
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The Editorial Office of Chinese Journal of Food Hygiene
2020-11-01
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Series: | Zhongguo shipin weisheng zazhi |
Subjects: | |
Online Access: | http://www.zgspws.com/zgspwszzen/article/abstract/20200608 |
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author | Shan WANG Liang SU Yuanli LIU Xiaowan WANG |
author_facet | Shan WANG Liang SU Yuanli LIU Xiaowan WANG |
author_sort | Shan WANG |
collection | DOAJ |
description | Objective To construct and compare the methods for correlation analysis of different elements in rice, including barium, vanadium, cadmium, lithium, aluminum, manganese, lead, thallium, antimony, copper, selenium, ehromium, mercury and arsenic. Methods Analyze the correlation among the fourteen elements in rice by two methods: Pearson correlation coefficient and partial correlation coefficient, and compare the two methods. Results Both of the methods can find the correlations among various pollutants from the data and have their own characteristics on computational complexity, information abundancy and other aspects: Pearson correlation coefficient method has less computation, but also provides less information; Partial correlation coefficient provides more information but needs more samples and computing resources. The Pearson correlation coefficient method showed the positive correlation elements including barium-vanadium, barium-lead, vanadium-lithium, aluminum-antimony and copper-thallium. There was no significant correlation between the remaining elements. The partial correlation coefficient method showed strong positive correlation including vanadiumbarium, lead-barium, total mercury-barium and antimony-aluminum. There was no significant correlation between the remaining elements. Conclusion Under the current data and software, hardware conditions, the correlation analysis of the partial correlation coefficient is recommended. |
first_indexed | 2024-03-12T21:03:22Z |
format | Article |
id | doaj.art-c70e1d0c7bac4922bffc187109084921 |
institution | Directory Open Access Journal |
issn | 1004-8456 |
language | zho |
last_indexed | 2024-03-12T21:03:22Z |
publishDate | 2020-11-01 |
publisher | The Editorial Office of Chinese Journal of Food Hygiene |
record_format | Article |
series | Zhongguo shipin weisheng zazhi |
spelling | doaj.art-c70e1d0c7bac4922bffc1871090849212023-07-31T02:32:12ZzhoThe Editorial Office of Chinese Journal of Food HygieneZhongguo shipin weisheng zazhi1004-84562020-11-01320663163510.13590/j.cjfh.2020.06.0081004-8456(2020)06-0631-05Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in riceShan WANG0Liang SU1Yuanli LIU2Xiaowan WANG3School of Public Health, Peking Union Medical College, Beijing 100730, ChinaChina National Center for Food Safety Risk Assessment, Beijing 100022, ChinaSchool of Public Health, Peking Union Medical College, Beijing 100730, ChinaInstitute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, ChinaObjective To construct and compare the methods for correlation analysis of different elements in rice, including barium, vanadium, cadmium, lithium, aluminum, manganese, lead, thallium, antimony, copper, selenium, ehromium, mercury and arsenic. Methods Analyze the correlation among the fourteen elements in rice by two methods: Pearson correlation coefficient and partial correlation coefficient, and compare the two methods. Results Both of the methods can find the correlations among various pollutants from the data and have their own characteristics on computational complexity, information abundancy and other aspects: Pearson correlation coefficient method has less computation, but also provides less information; Partial correlation coefficient provides more information but needs more samples and computing resources. The Pearson correlation coefficient method showed the positive correlation elements including barium-vanadium, barium-lead, vanadium-lithium, aluminum-antimony and copper-thallium. There was no significant correlation between the remaining elements. The partial correlation coefficient method showed strong positive correlation including vanadiumbarium, lead-barium, total mercury-barium and antimony-aluminum. There was no significant correlation between the remaining elements. Conclusion Under the current data and software, hardware conditions, the correlation analysis of the partial correlation coefficient is recommended.http://www.zgspws.com/zgspwszzen/article/abstract/20200608riceelementcorrelation analyze |
spellingShingle | Shan WANG Liang SU Yuanli LIU Xiaowan WANG Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice Zhongguo shipin weisheng zazhi rice element correlation analyze |
title | Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
title_full | Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
title_fullStr | Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
title_full_unstemmed | Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
title_short | Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
title_sort | application of pearson and partial correlation coefficient model in the research of heavy metal pollution in rice |
topic | rice element correlation analyze |
url | http://www.zgspws.com/zgspwszzen/article/abstract/20200608 |
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