An outlier is a data point on the extreme end of your dataset. It could be very large or very small, but it is abnormally different from most of the other values in your dataset. There are many reasons for outliers, and they can show up in any kind of study.
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Grubbs' Test, or the extreme studentized deviant (ESD) method, is a simple technique to quantify outliers in your study. It is based on a normal distribution and a test statistic (Z) that is calculated from the most extreme data point. The test statistic corresponds to a p-value that represents the likelihood of seeing that outlier assuming the underlying data is Gaussian.
Outliers lend themselves to graphics perhaps more than any other aspect of statistics. Scatter plots, box plots, and violin plots are common ways to see where your dataset clumps together and which values are the extremes.
Enjoying this calculator? Prism offers more capabilities for outlier detection, including methods like Grubbs' Test, ROUT, and more. We offer a free 30-day trial of Prism and its publication-ready graphic creation.
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