You cannot, unless they are all outliers, and the plot records outliers separately.
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
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.
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.
Having only the mean is not sufficient to identify outliers. You need some measure of dispersion.
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.
You cannot, unless they are all outliers, and the plot records outliers separately.
there are no limits to outliers there are no limits to outliers
The ISBN of Outliers - book - is 9780316017923.
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
"Outliers" by Malcolm Gladwell has approximately 320 pages in its paperback edition.
Outliers - book - was created on 2008-11-18.
There is no universally agreed definition of an outlier. One conventional definition of an outlier classifies an observations x as an outlier if: x > Q3 + 1.5*IQR = Q3 + 1.5*(Q3 - Q1) A similar definition applies to outliers that are too small. So, to find the maximum that is not an outlier, you need to find the upper and lower quartiles (Q3 and Q1 respectively) and then find the largest observation that is smaller than Q3 + 1.5*IQR = Q3 + 1.5*(Q3 - Q1)
Outliers - 2010 was released on: USA: 5 February 2010
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.
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.