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DA0-002 Data Analysis Practice Question

A data analyst is summarizing the central tendency of a dataset with extreme outliers. Which measure is most robust to outliers?

⚠ Common exam trap

Candidates often confuse measures of central tendency with measures of dispersion, and assuming that the mean is always the best measure of center. Candidates often pick the mean out of habit, ignoring its sensitivity to outliers.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Median

The median is the middle value when data is ordered, so extreme outliers (whether very high or very low) do not affect its position. Unlike the mean, which incorporates every value and can be pulled strongly by outliers, the median remains stable. Therefore, for a dataset with extreme outliers, the median is the most robust measure of central tendency.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Standard deviation

    Why it's wrong here

    Standard deviation measures dispersion around the mean and is strongly inflated by extreme outliers, since each deviation is squared. It suits datasets that are roughly symmetric and outlier-free. Summarising central tendency under outliers calls for the median, which resists skewed values.

  • ✓

    Median

    Why this is correct

    The median is positional, not arithmetic: it depends only on the middle value's rank, so extreme outliers cannot drag it. The mean incorporates every value's magnitude, making it highly sensitive to skew. For skewed data, the median better represents typical central tendency.

  • ✗

    Mean

    Why it's wrong here

    The mean sums every value and divides by the count, so a single extreme outlier drags it away from the centre; the median, by contrast, depends only on rank position. The mean is tempting because it uses all data points and suits symmetric distributions without extreme values, where it equals the median.

  • ✗

    Range

    Why it's wrong here

    Range is a measure of spread, not central tendency, and is highly sensitive to extreme values since it uses only the maximum and minimum. It would be chosen when describing total variability. For central tendency with outliers, the median is the robust measure.

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Last reviewed September 2026 · checked against the official CompTIA exam blueprint

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