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DA0-002 Data Acquisition and Preparation Practice Question

In a dataset of employee salaries, the analyst notices one value that is significantly higher than the rest. Using the IQR method, which values are typically considered 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

✓

Values beyond Q1 - 1.5*IQR or Q3 + 1.5*IQR

Outliers are values less than Q1 - 1.5*IQR or greater than Q3 + 1.5*IQR.

Answer analysis

Option-by-option breakdown

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

  • ✗

    Values beyond Q1 - 3*IQR or Q3 + 3*IQR

    Why it's wrong here

    The IQR method flags outliers beyond Q1 - 1.5*IQR or Q3 + 1.5*IQR; the 3*IQR multiplier describes extreme outliers, not the standard threshold. The 1.5 multiplier is the conventional Tukey fence applied to salary distributions.

  • ✓

    Values beyond Q1 - 1.5*IQR or Q3 + 1.5*IQR

    Why this is correct

    Values falling below Q1 − 1.5×IQR or above Q3 + 1.5×IQR are flagged as outliers, satisfying the stem's requirement to identify the salary that sits significantly higher than the rest. Tukey's fences define this boundary, so an extreme high salary exceeding Q3 + 1.5×IQR is correctly detected.

  • ✗

    Values beyond mean ± 2 standard deviations

    Why it's wrong here

    Mean ± 2 standard deviations is a z-score heuristic assuming normality, not the IQR method. IQR fences sit at Q1 - 1.5*IQR and Q3 + 1.5*IQR, derived from quartiles and resistant to the very extreme salary values being detected.

  • ✗

    Values beyond min and max

    Why it's wrong here

    Minimum and maximum are the dataset's extremes, so nothing can fall beyond them; this defines the range, not an outlier boundary. The IQR method places fences at Q1 - 1.5*IQR and Q3 + 1.5*IQR, which can sit inside the observed min and max.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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