DA0-002 Visualization and Reporting Practice Question
A data analyst creates a bubble chart showing country GDP (x-axis), life expectancy (y-axis), and population (bubble size). However, large bubbles overlap and obscure many data points. Which corrective action should the analyst take?
⚠ Common exam trap
Test-takers frequently choose to reduce bubble sizes uniformly (Option C) thinking it solves overlap, but this distorts the proportional encoding of population, whereas opacity preserves the original data relationships while improving visibility.
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
✓
Set bubble opacity to 70%
Setting bubble opacity to 70% allows overlapping bubbles to become semi-transparent, so data points underneath remain visible. This technique preserves the original data representation (GDP, life expectancy, and population) without altering the chart's scale or removing data. It is a standard visualization practice for handling overplotting in dense scatter plots and bubble charts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the chart canvas size
Why it's wrong here
Larger canvas doesn't prevent overlap if bubbles are large.
- ✓
Set bubble opacity to 70%
Why this is correct
Transparency allows seeing through overlapping bubbles.
- ✗
Reduce all bubble sizes uniformly
Why it's wrong here
Smaller bubbles may make small populations invisible.
- ✗
Remove outlier countries with large populations
Why it's wrong here
Removing data is not recommended; skews analysis.
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