Question:
Which measure of central tendency is better suited for dealing with an outlier?
Which measure of central tendency is better suited for dealing with an outlier?
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Mean is sensitive to outliers.
Median is robust/resistant to outliers.
Always prefer the median for skewed data or datasets containing extreme anomalies.
Median is robust/resistant to outliers.
Always prefer the median for skewed data or datasets containing extreme anomalies.
Updated On: Sep 7, 2026
- Median
- Mean
- Mode
- Range
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The Correct Option is A
Solution and Explanation
Concept:
Measures of central tendency summarize an entire dataset with a single representative value.
An outlier is an extreme data point that lies an abnormal distance from other values in a random sample.
Step 1: Evaluating the Impact of Outliers on Different Measures:
- The Mean incorporates the numerical value of every observation in its formula (\(\sum x / n\)). Consequently, extreme values pull the mean significantly in their direction, distorting the central tendency.
- The Median is a positional average determined strictly by ordering the dataset and selecting the middle element. Changing an extreme value does not affect the middle position, making it highly robust against outliers.
- The Mode represents the most frequently occurring value. However, a dataset may not have a mode or may have multiple modes, making it unreliable as a primary central measure for numeric distributions with outliers.
- The Range measures dispersion (Maximum \(-\) Minimum) rather than central tendency and is severely impacted by outliers.
Step 2: Conclusion:
Because the median is resistant to skewness and extreme values, it is the preferred measure of central tendency when outliers are present.
Final Answer:
Therefore, the Median is the most suitable measure. The correct option is (A).
Measures of central tendency summarize an entire dataset with a single representative value.
An outlier is an extreme data point that lies an abnormal distance from other values in a random sample.
Step 1: Evaluating the Impact of Outliers on Different Measures:
- The Mean incorporates the numerical value of every observation in its formula (\(\sum x / n\)). Consequently, extreme values pull the mean significantly in their direction, distorting the central tendency.
- The Median is a positional average determined strictly by ordering the dataset and selecting the middle element. Changing an extreme value does not affect the middle position, making it highly robust against outliers.
- The Mode represents the most frequently occurring value. However, a dataset may not have a mode or may have multiple modes, making it unreliable as a primary central measure for numeric distributions with outliers.
- The Range measures dispersion (Maximum \(-\) Minimum) rather than central tendency and is severely impacted by outliers.
Step 2: Conclusion:
Because the median is resistant to skewness and extreme values, it is the preferred measure of central tendency when outliers are present.
Final Answer:
Therefore, the Median is the most suitable measure. The correct option is (A).
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