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Q: How do you identify outliers?

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There is no limit to the number of outliers there can be in a set of data.

apparently there is no limit to outliers. at least according to everybody else's answers.

It is not.

Deviation-based outlier detection does not use the statistical test or distance-based measures to identify exceptional objects. Instead, it identifies outliers by examining the main characteristics of objects in a group.

Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)

Related questions

there are no limits to outliers there are no limits to outliers

Having only the mean is not sufficient to identify outliers. You need some measure of dispersion.

The ISBN of Outliers - book - is 9780316017923.

Outliers - book - has 304 pages.

There is no limit to the number of outliers there can be in a set of data.

Outliers - book - was created on 2008-11-18.

apparently there is no limit to outliers. at least according to everybody else's answers.

Outliers - 2010 was released on: USA: 5 February 2010

There is no agreed definition of an outlier and consequently, there is no simple answer to the question. The number of outliers will depend on the criterion used to identify them. If you have observations from a normal distribution, you should expect around 1 in 22 observations to be more than 2 standard deviations from the mean, and about 1 in 370 more than 3 sd away. You will have more outliers if the distribution is non-normal - particularly if it is skewed.

maybe!!

1,5

There is no agreed definition of outliers. However two common criteria to identify outliers are: Method I: If Q1 is the lower quartile and Q3 the upper quartile then any number smaller than Q1 - 1.5*(Q3 - Q1) or larger than Q3 + 1.5*(Q3 - Q1) is an outlier. By that criterion there is no outlier. Method II: Assume the numbers are normally distributed. then outliers are with absolute z-scores greater than 1.96. Again, there are no outliers.

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