Statistical analysis of discrepant radioecological data using Monte Carlo Bootstrap Method

被引：6

作者：

Casado da Silva, Arykerne Nascimento ^{[1
]}

Amaral, Romilton dos Santos ^{[1
]}

dos Santos Junior, Jose Araujo ^{[1
]}

Vieira, Jose Wilson ^{[2
,3
]}

Cezar Menezes, Romulo Simoes ^{[1
]}

机构：

[1] Univ Fed Pernambuco, Dept Nucl Energy, BR-50740540 Recife, PE, Brazil

[2] Fed Educ Sci & Technol Inst Pernambuco, BR-50740540 Recife, PE, Brazil

[3] Univ Fed Pernambuco, Polytech Sch Pernambuco, BR-50720001 Recife, PE, Brazil

来源：

JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY | 2015年 / 306卷 / 03期

关键词：

Monte Carlo; Bootstrap; Radioecological data; Resampling;

D O I：

10.1007/s10967-015-4207-1

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

This study was developed aiming to apply the Monte Carlo Bootstrap Method in statistical analysis of radioecological data and to obtain appropriate predictors for the population parameters. Only fourteen samples of Ra-226 in prickly pear were used. These samples presented Ra-226 concentrations ranging from 1.495 to 25.000 Bq kg(-1) in the dry matter with an arithmetic average of 5.966 +/- A 5.903 Bq kg(-1). The resampling procedure obtained an average of 6.014 +/- A 1.597 Bq kg(-1), a value more representative because the outliers did not influence its calculation. Therefore, the method has valid and fundamental application for statistical analysis in radioecology.

引用

页码：571 / 577

页数：7

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