Which statement best defines an outlier in a data set?

Which statement best defines an outlier in a data set?

• A. A data point that is always near the mean.
• B. A data point that is the median value.
• C. A data point that does not affect the distribution.
• D. A data point significantly different from the rest.

Answer: (D)

An outlier is a data point that stands apart because it is far from the other observations. The option that says a data point is significantly different from the rest captures this idea best, since it describes a value that doesn’t fit the common pattern of the data. This matters because such a point can pull the average toward itself and can change the distribution’s shape, indicating unusual variation or potential measurement error. A data point near the mean isn’t an outlier, and being the median value describes a central location, not an exception. And saying an outlier doesn’t affect the distribution isn’t accurate, since outliers often influence metrics like the mean and the overall spread.

An outlier is a data point that stands apart because it is far from the other observations. The option that says a data point is significantly different from the rest captures this idea best, since it describes a value that doesn’t fit the common pattern of the data.

This matters because such a point can pull the average toward itself and can change the distribution’s shape, indicating unusual variation or potential measurement error. A data point near the mean isn’t an outlier, and being the median value describes a central location, not an exception. And saying an outlier doesn’t affect the distribution isn’t accurate, since outliers often influence metrics like the mean and the overall spread.