title: Analysis of statistical outliers with application to whole effluent toxicity testing.
abstract: In this analysis, low-value outliers were detected in five data sets obtained from laboratory records. The effect of removing the outliers by three methods data rejection (asymmetrical and symmetrical trimming and Winsorization) revealed that all three methods slightly increased the mean and reduced the variance of the data sets. These opposing effects on the results of a hypothesis test of means were examined in the context of passing or failing a regulatory requirement significant difference between effluent concentration and a control. Analysis by statistical resampling of one data set showed that while all data rejection methods reduced the level of Type II error in a hypothesis test of no difference in reproduction between a test concentration and a regulatory limit, asymmetrical trimming was the best in this regard.
authors.affiliation: King County-Metro Environmental Laboratory, Seattle, Washington 98119-1507, USA.
authors.forename: J A
authors.initials: JA
authors.lastname: Buckley
authors.forename: T D
authors.initials: TD
authors.lastname: Georgianna
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D003445:Crustacea / Q000254:growth & development; D003627:Data Interpretation, Statistical; D004463:Ecology; D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D015233:Models, Statistical; D013223:Statistics as Topic / Q000379:methods*; D018675:Toxicity Tests