What term describes an extreme value far from the center of a distribution?

What term describes an extreme value far from the center of a distribution?

• A. Outlier
• B. Skewness
• C. Positive Skew
• D. Negative Skew

Answer: (A)

An outlier is an observation that lies far from the center of the data. It stands apart from the bulk of the values, often detected using rules like 1.5 times the interquartile range beyond the quartiles or a Z-score beyond a threshold. This term specifically describes a single extreme value or a small number of extreme values, rather than the overall shape of the distribution. Skewness, by contrast, describes how the distribution's shape is asymmetrical. Positive skew means the right tail is longer, and negative skew means the left tail is longer. Those describe the overall tendency of the data, not a lone extreme observation.

An outlier is an observation that lies far from the center of the data. It stands apart from the bulk of the values, often detected using rules like 1.5 times the interquartile range beyond the quartiles or a Z-score beyond a threshold. This term specifically describes a single extreme value or a small number of extreme values, rather than the overall shape of the distribution.

Skewness, by contrast, describes how the distribution's shape is asymmetrical. Positive skew means the right tail is longer, and negative skew means the left tail is longer. Those describe the overall tendency of the data, not a lone extreme observation.