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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 in box and whisker plot?
To find the limits of outliers in box and whisker plots, you first must determine the Interquartile Range. The Interquartile Range is the difference between the Upper Quartile and the Lower Quartile. For instance, if my Upper Quartile = 87 and my Lower Quartile is 52, then 87 - 52= 35. 35 is the Interquartile Range (IQR).Next, you use the formula 1.5 x IQR to determine if you have any outliers.Example:1.5 x 35 = 52.5Now determine the limit for the Upper Quartile by adding 52.5 to the Upper Quartile.Example:52.5 + 87 = 139.5139.5 is the limit for the Upper Quartile.Next, determine the limit for the Lower Quartile by subtracting the Lower Quartile from 52.5Example52 - 52.5 = -0.5-0.5 is the limit for the Lower QuartileThus, the LIMITS are -0.5 and 139.5. In order for a number to be considered an outlier, it must either be less than -0.5 or greater than 139.5
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.
