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Is the interquartile range or IQR is found by subtracting the mean from the maximum value of a data set?
No. The IQR is found by finding the lower quartile, then the upper quartile. You then minus the lower quartile value from the upper quartile value (hence "interquartile"). This gives you the IQR.
What is an outlier in stats?
An outlier, in a set of data, is an observation whose value is distant from other observations. There is no exact definition but one commonly used definition is any value that lies outside of Median ± 3*IQR IQR = Inter-Quartile Range.
How can you use a calculation to decide whether a data point is an outlier in a data set?
The exact definition of which points are considered to be outliers is up to the experimenters. A simple way to define an outlier is by using the lower (LQ) and upper (UQ) quartiles and the interquartile range (IQR); for example: Define two boundaries b1 and b2 at each end of the data: b1 = LQ - 1.5 × IQR and UQ + 1.5 × IQR b2 = LQ - 3 × IQR and UQ + 3 × IQR If a data point occurs between b1 and b2 it can be defined as a mild outlier If a data point occurs beyond b2 it can be defined as an extreme outlier. The multipliers of the IQR for the boundaries, and the number of boundaries, can be adjusted depending upon what definitions are required/make sense.
How does one find if any data points are an outlier on the high end of a distribution?
There is no formal definition of a outlier: it is a data point that is way out of line wit the remaining data set.If Q1 and Q3 are the lower and upper quartiles of the data set, then (Q3 - Q1) is the inter quartile range IQR. A high end outlier is determined by a value which is larger thanQ3 + k*IQR for some positive value k. k = 1.5 is sometimes used.
Calculated by subtracting the smallest value in the data set from the largest value in the data set?
The range is the size of the set of data. Take the smallest from the largest value to get the range
