Most Prominent Methods of How to Find Outliers in Statistics

Extreme values are data values that are very different from most specific data sets. These data values fall within the general trend, which is already in the data. Extreme values are too low or too high in a specific data set that can create an error in your statistics. For example, if someone measures the length of a child's nose, its common value may be whether Pinocchio is included in a specific class of data values.

It is necessary to examine the data set provided to study extreme values in statistics and how to find extreme values in statistics that can cause some challenges. Although this can be easily identified using a radical graph in which some values differ from the specific values of the data. So, how much variability is the value as an external value? We will study a specific analysis that provides an external standard on what develops a data deviation.

What are outliers in statistics?

The definition of extreme values in statistics can be considered as a data section, which is used to represent an unusual interval from one point to another. Or we can say that the data is the ones that remain outside the other given values with a data set. If someone has pinocchio in a group of teenagers, the length of the nose will be considered far away, compared to other children.

Examples of outliers in statistics

5, 94, 95, 96, 99, 104, 105, 199

"5" is studied as a very small value, while "199" is recognized as a very high value. However, extreme values are not always taken as simple values. Let's say someone before the checks selected last month:

$220, $245, $20, $230.

Your salary. is considered 130 USD. But the lower salary ($20) may be because that person has gone on holiday; therefore, an average weekly salary is USD 130, which is not a real representation of their earnings. Their average is more like $232 if previous data ($20) in the given data set is accepted. The data set could be similar to:

60, 9, 31, 18, 21, 28, 35, 13, 48, 2

One can guess that 2 are remote and probably 60. But it's expected that 60 will be in the data set.

How to find the outliers in statistics using the Tukey method?

Tukey's method of detecting extreme values in statistics applies the Interquartile range to separate very small or very large numbers. It is equivalent to the above method, but formulas that consist slightly differently can be examined and the specifications are slightly different. For example, the Toki method uses the idea of "fences".

Conclusion

Many students have difficulty finding extreme values in statistics, so I mentioned two different ways to calculate them. In addition, there are other advanced ways to get the value of extreme values, such as the Dixon Q test, generalized ESD, and more. Use the IQR and Tukey method mentioned above to resolve issues of extreme value.

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