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Z-Score: A Handy Tool for Detecting Outliers in Data - MSN
Outlier Detection The z-score is used to identify outliers in a dataset. Any data point with a z-score greater than 3 or less than -3 is considered an outlier.
At least 5% of data even in a reasonably high quality data set will likely contain anomalies—odd as these data might be, it is more peculiar not to find them than to identify them. More formally ...
We propose a procedure for the detection of multiple outliers in multivariate data. Let X be an n × p data matrix representing n observations on p variates. We first order the n observations, using an ...
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