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ABSTRACT Environmental research data usually present high variability because of the presence of outlier values. This study sought to apply the interval bootstrap method, as compared to Chebyshev’s Theorem, for… Click to show full abstract
ABSTRACT Environmental research data usually present high variability because of the presence of outlier values. This study sought to apply the interval bootstrap method, as compared to Chebyshev’s Theorem, for the statistical assessment of environmental data with anomalous values. The results obtained showed that: (a) the bootstrap method is an excellent alternative in the assessment of environmental data with outliers; (b) the method percentile bootstrap (Boot-perc-s) presented the lower interval amplitude to the concentrations of 226Ra, and (c) Chebyshev’s Theorem presented the highest interval amplitude for the concentration of 226Ra.
Journal Title: International Journal of Environmental Studies
Year Published: 2019
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