On Abandoning Hypothesis Testing in Environmental Standard Compliance Assessment
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We use basic characteristics of statistical significance test to argue the abandonment of hypothesis testing in environmental standard (or criterion) compliance assessment. The typical sample size used for environmental assessment is small, and the natural variation of many water quality constituent concentrations is high. These conditions lead to low statistical power of the hypothesis tests used in the assessment process. As a result, using hypothesis testing is often inefficient in detecting noncompliance. When a noncompliance is detected, it is frequently due to sampling or other types of error. We illustrate the problems using two examples, through which we argue that these problems cannot be resolved under the current practice of assessing compliance one water at a time. We recommend that the hypothesis testing framework be replaced by a statistical estimation approach, which can more effectively leverage information from assessments on similar waters using a probabilistic assessment approach.
Keywords303(d) listing Compliance assessment Nutrient criteria Statistics
We thank Lei Zheng, David Pfeifer, and two anonymous reviewers for helpful comments and discussion.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no conflict of interest.
- Efron B, Morris C (1973a) Stein’s estimation rule and its competitors – an empirical Bayes approach. J Am Stat Assoc 68(341):117–130Google Scholar
- Efron B, Morris C (1973b) Combining possibly related estimation problems. J R Stat Soc Ser B (Methodol) 35(3):379–421Google Scholar
- FDEP Overview of approaches for numeric nutrient criteria development in ma371 rine waters (2011) Technical report, Florida Department of Environmental Protection, Division of Environmental Assessment and Restoration, Standards and Assessment Section, Tallahassee, FLGoogle Scholar
- McElreath R (2016) Statistical rethinking: A Bayesian course with examples in R and Stan. Chapman & Hall/CRC Press, CRC Press, Boca Raton, FLGoogle Scholar
- Ott WR (1995) Environmental statistics and data analysis. Lewis Publishers, Boca RatonGoogle Scholar
- Qian SS (2016) Environmental and ecological statistics with R, 2nd edn. Chapman and Hall/CRC Press, CRC Press, Boca Raton, FLGoogle Scholar
- Stephan CE, Mount DI, Hansen DJ, Gentile JR, Chapman GA, Brungs WA (1985) Guidelines for deriving numerical water quality criteria for the protection of aquatic organisms and their uses. US Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, Number 822R85100Google Scholar