Yes, but it will cause data corruption and/or abnormal program termination. Don't do it.
Not necessarily. If the data are not ordered by size, it could be anywhere in the data set. If the data are ordered, it could be the last. But equally, it could be the first. Also, it could be the last two, three etc, or one from each end. Essentially, an outlier is a value that is an "abnormal" distance from the "middle". The middle may be the median or the mean of the data set (usually not the mode). The "abnormal" distance is generally defined in terms of a multiple of the interquartile range (when median is used) or standard deviation (when the mean is used).
Standard deviation can be calculated using non-normal data, but isn't advised. You'll get abnormal results as the data isn't properly sorted, and the standard deviation will have a large window of accuracy.
A standard distribution regards 95% of all data being within 2-standard deviations of either side. Similarly, within one standard deviation either way is 68% of all data. This creates a bell curve distribution. An abnormal distribution would be erratic and not follow such a statistical structure of representation.
One approach that has not been commonly used to define abnormal behavior is a strict reliance on anecdotal evidence or personal beliefs. While personal experiences can be informative, they may not always capture the complexity and diversity of abnormal behaviors observed across different cultures, contexts, and individuals. It is essential to incorporate scientific research, empirical data, and psychological theories in defining abnormal behavior to ensure accuracy and reliability.
Abnormal
wbc esterace 2+ Abnormal occult blood 1+ Abnormal wbc 11-30 Abnormal rbc 4-10 Abnormal
As a noun, an abnormal is a person or object which is not normal.
Both.
That figure is abnormal.
"Abnormal" is an adjective.
Abnormal