Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal. Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers. Another motivation is to provide methods with good performance when there are small departures from parametric distributions. For example, robust methods work well for mixtures of two normal distributions with different standard-deviations; under this model, non-robust methods like a t-test work poorly.
Welcome to ''Robust Methods'' subject guide. Subject guides are lists of resources created by librarians to assist students with their research needs. These list of resources may include topics but not limited to books, journals, databases, websites, as well as any other topics the librarian feels would assist students with their research.
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