Abstract
This review summarizes critically the approaches available to the treatment of suspect outlying results in sets of experimental measurements. It covers the use of parametric methods such as the Dixon test (with comments on the problems of multiple outliers); the application of non-parametric statistics based on the median to by-pass outlier problems; and the application of robust statistical methods, which down-weight the importance of outliers. The extension of these approaches to outliers occurring in regression problems is also surveyed.

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