DA0-002 Visualization and Reporting Practice Question
A data analyst needs to visualize the distribution of salaries across departments and also compare the median and identify outliers. Which chart type is most suitable?
⚠ Common exam trap
Watch out — candidates often confuse 'distribution' with 'comparison of summary statistics' — candidates pick histogram because it shows distribution, but only a box plot simultaneously shows median and outliers across multiple groups.
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
✓
Box plot
A box plot is purpose-built for exactly this task: it displays the five-number summary (minimum, Q1, median, Q3, maximum) and plots points beyond 1.5×IQR as outliers. This lets an analyst compare medians and spread across departments side-by-side while visually flagging outliers in one view.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Box plot
Why this is correct
A box plot encodes median, quartiles and whiskers on one axis, exposing salary distribution per department and flagging outliers beyond the whiskers. It satisfies the stem's dual requirement to compare medians and identify outliers simultaneously.
- ✗
Histogram
Why it's wrong here
A histogram shows the shape of one variable's distribution, but it bins a single continuous field and cannot compare medians across departments or flag individual outliers. It suits examining the frequency distribution of one measure, not side-by-side departmental comparison.
- ✗
Bar chart
Why it's wrong here
A bar chart compares an aggregate value across categories, so it displays departmental medians but hides the underlying distribution and individual outliers. It is correct when the goal is comparing a summary statistic between groups, not showing spread within each group.
- ✗
Scatter plot
Why it's wrong here
A scatter plot plots paired numeric variables to reveal correlation between two measures, so it cannot show a single salary distribution's shape, median or outliers. It is the right choice when testing whether one continuous variable predicts another, such as salary against years of experience.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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