What defines an outlier in a data set?

An outlier in a data set is defined as a value that is unusually small or large compared to the rest of the data. This unusual characteristic is often identified using statistical measures that indicate how far a particular value is from the average or central trend of the data set. Outliers can significantly affect statistical analyses, impacting calculations such as means and standard deviations, and recognizing them is essential for accurate data interpretation and decision-making.

When identifying outliers, common approaches include examining values that fall outside certain thresholds, such as those defined by standard deviations from the mean or the interquartile range method, which considers values that lie significantly outside the first and third quartiles. Thus, the defining criterion for an outlier is its extreme nature compared to the distribution of the data values.