Which term refers to data values that lie far from the rest of the dataset, typically defined as more than 1.5 times the IQR from the quartile boundaries?

• A. Outliers
• B. Range
• C. Semi-interquartile range
• D. Standard deviation

Answer: (A)

This question tests recognizing data values that stand apart from the rest of the data. These distinct values are identified using the boxplot rule: anything more than 1.5 times the IQR away from the quartile boundaries is considered an outlier. The IQR is the range of the middle 50% of the data (the difference between the third and first quartiles). For example, if Q1 is 10 and Q3 is 20, the IQR is 10, so 1.5 IQR is 15. The bounds become 10 − 15 = −5 and 20 + 15 = 35; any values outside this interval are outliers.

Other measures don’t specifically flag unusual values in this way. The range just measures overall spread between min and max, not thresholds for extreme values. The semi-interquartile range is half the IQR and is a spread measure, not a criterion for outliers. Standard deviation looks at dispersion around the mean and likewise doesn’t use the 1.5 IQR rule.

So the term described is outliers.