Two standard deviations above the mean are also used to define outliers.

• A. True
• B. False
• C. Sometimes
• D. Not specified

Answer: (A)

Outliers are often identified by how far a value lies from the center of the data, measured in units of standard deviation. In datasets that are approximately normally distributed, a value that lies more than two standard deviations above the mean (mean + 2*SD) flags an unusually high observation, and the same idea applies for values more than two standard deviations below the mean. So using two standard deviations above the mean as a cutoff to mark potential outliers is a common, straightforward rule of thumb. It’s a quick screening method, though for non-normal data or different contexts other criteria (like three SDs or the 1.5 IQR rule) might be more appropriate.