They are observations with a low likelihood of occurrence. They may be called outliers but there is no agreed definition for outliers.
You may be referring to the statistical term 'outlier(s)'. Also, there is a rule in statistics called the '68-95-99 Rule'. It states that in a normally distributed dataset approximately 68% of the observations will be within plus/minus one standard deviation of the mean, 95% within plus/minus two standard deviations, and 99% within plus/minus three standard deviations. So if your data follow the classic bell-shaped curve, roughly 1% of the measures should fall beyond three standard deviations of the mean.
Measurements. Just because a particular result lies far from the mean doesn't make it any different. If it's noticeably far from the "crowd" of all the other measurements, it can be called an outlier. An outlier isn't necessarily bad, just different. It should be examined in detail to see if there's something odd about it, but not discarded out of hand.
It is a measurement which may, sometimes, be called an extreme observation or an outlier. However, there is no agreed definition for outliers.
It is not called anything special, just 2 standard deviations or 3 sd.
All measurements are made by merely comparing the object to be measured with a known object which is called the standard , or reference.
20X26 It is called a standard pillow case
Values that are either extremely high or low in a data set are called 'outliers'. They are typically 3 standard deviations or more from the mean.
It is called measurement. By comparing a specific aspect of an object with a standard unit, you can quantify the attribute in terms of the unit of measurement.
A standard unit of measurement is the unit (size or quantity) that is agreed upon in that nation or trading partnership. In science the standard units of measurement are called SI units. (An international standard). This is the metric system.
Megalencephaly (also called macrencephaly) describes an enlarged brain whose weight exceeds the mean (the average weight for that age and sex) by at least 2.5 standard deviations (a statistical measure of variation).
The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,