Robust methods are useful for dealing with outliers from "summary" of Statistics for Censored Environmental Data Using Minitab and R by Dennis R. Helsel
Robust methods can be particularly helpful when dealing with outliers in environmental data. Outliers are data points that are significantly different from the rest of the data, and they can skew the results of statistical analyses. Traditional statistical methods are sensitive to outliers, which can lead to inaccurate conclusions. Robust methods, on the other hand, are less influenced by outliers and provide more reliable results in the presence of extreme values. These methods are designed to be more resistant to the effects of outliers, making them a valuable tool for analyzing environmental data that may contain outliers. In environmental studies, outliers are not uncommon due to the complex nature of environmental systems. These outliers can be caused by a variety of factors, such as measurement error...
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