Bootstrap interval with application in environmental monitoring

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.

KEYWORDS:

• Radioecology
• resampling
• Monte Carlo
• statistical modelling

Disclosure statement

No potential conflict of interest was reported by the authors.