An outlier is best described as:

An outlier is best described as:

• A. An observation very similar to the rest
• B. An observation very different from most others that biases statistics
• C. A data point that fits the model perfectly
• D. A measurement error that should always be corrected

Answer: (B)

Outliers are observations that stand apart from the rest of the data and can pull statistics in unusual directions. The option that describes an observation very different from most others and that biases statistics captures the essence: such a point can distort measures like the mean, standard deviation, and relationships in analyses. The other descriptions don’t fit: being very similar to the rest isn’t an outlier; a point that fits the model perfectly isn’t an outlier; and a measurement error isn’t automatically something to always correct—outliers may be genuine values, and whether to adjust or exclude them depends on the context.

Outliers are observations that stand apart from the rest of the data and can pull statistics in unusual directions. The option that describes an observation very different from most others and that biases statistics captures the essence: such a point can distort measures like the mean, standard deviation, and relationships in analyses. The other descriptions don’t fit: being very similar to the rest isn’t an outlier; a point that fits the model perfectly isn’t an outlier; and a measurement error isn’t automatically something to always correct—outliers may be genuine values, and whether to adjust or exclude them depends on the context.