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Excel does not have built in functions for outlier identification. However, if you want to identify quickly data that is in the very low or high range, then use the sort routine in Excel. You can make a scatter plot to identify points distant from the normal scattering. I've also included a related link, which shows some tests of outliers, which can be implemented using the functions in Excel. The Chauvenet's criteria involves use of normal distribution, available in Excel, to identify the probability of data points. An outlier is not necessarily an erroneous number. See related link. It is just a number that is distant from others the set. However, if there is some physical limit on your data, then you might want to screen for numbers beyond this limit. For example, you are measuring heights of men, so you will want to screen you data for heights too big or too small as possible data errors. Certainly, if you find a 600 ft person, you know that this outlier was an error, like forgetting a decimal point.
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How do you find clusters on a box and whisker plot?
You cannot, unless they are all outliers, and the plot records outliers separately.
How do you find the limit of outliers?
You don't do anything. There is none!!
What does the whisker in a box-and-whisker plot represent?
The whiskers mark the ends of the range of figures - they are the furthest outliers. * * * * * No. Outliers are not part of a box and whiskers plot. The whiskers mark the ends of the minimum and maximum observations EXCLUDING outliers. Outliers, if any, are marked with an X.
Can you safely remove outliers from scatter charts?
You can only do it if either the outliers are way out - so far that they must be odd, so far that there can be no argument, no need for statistics to prove them to be outliers, or you need to prove that they are outliers using statistics - something like Grubb's test. To do that, the simplest way is software.
How you find suspected outlier when you have mean?
Having only the mean is not sufficient to identify outliers. You need some measure of dispersion.
