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논문 기본 정보

자료유형
학술저널
저자정보
조홍연 (한국해양과학기술원) 이기섭 (부산대학교) 안순모 (부산대학교)
저널정보
한국해양과학기술원 Ocean and Polar Research Ocean and Polar Research Vol.38 No.2
발행연도
2016.6
수록면
149 - 159 (11page)
DOI
10.4217/OPR.2016.38.2.149

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The statistical measures of the coastal environmental data are used in a variety of statistical inferences, hypothesis tests, and data-driven modeling. If the measures are biased, then the statistical estimations and models may also be biased and this potential for bias is great when data contain some outliers defined as extraordinary large or small data values. This study aims to suggest more robust statistical measures as alternatives to more commonly used measures and to assess the performance these robust measures through a quantitative evaluation of more typical measures, such as in terms of locations, spreads, and shapes, with regard to environmental monitoring data in the Busan coastal sea. The detection of outliers within the data was carried out on the basis of Rosner’s test. About 5?10% of the nutrient data were found to contain outliers based on Rosner’s test. After removal (zero-weighting) of the outliers in the data sets, the relative change ratios of the mean and standard deviation between before and after outlierremoval conditions revealed the figures 13 and 33%, respectively. The variation magnitudes of skewness and kurtosis are 1.36 and 8.11 in a decreasing trend, respectively. On the other hand, the change ratios for more robust measures regarding the mean and standard deviation are 3.7?10.5%, and the variation magnitudes of robust skewness and kurtosis are about only 2?4% of the magnitude of the non-robust measures. The robust measures can be regarded as outlier-resistant statistical measures based on the relatively small changes in the scenarios before and after outlier removal conditions.

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