DA0-002 Data Governance Practice Question
A data analyst creates a scatter plot showing the relationship between advertising spend and revenue. The plot shows a strong positive correlation. Which of the following should the analyst include in the report to ensure accurate communication?
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
✓
Include a note that correlation does not imply causation.
Correlation does not imply causation. It is important for the analyst to include this caveat to prevent misinterpretation of the relationship. Option B is incorrect because a bar chart is not appropriate for showing the relationship between two continuous variables. Option C is incorrect because removing outliers without justification can distort the analysis; outliers should be handled transparently. Option D is incorrect because while a trend line could be added, it is not mandatory and the question specifically asks for ensuring accurate communication, which is primarily about the correlation-causation warning.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Include a note that correlation does not imply causation.
Why this is correct
A strong positive correlation between advertising spend and revenue does not establish that spending caused the revenue change; a confounding variable could drive both. Stating this caveat satisfies the accurate-communication requirement, preventing readers from inferring a causal relationship the scatter plot cannot support.
- ✗
Replace the scatter plot with a bar chart.
Why it's wrong here
A bar chart compares discrete categories, discarding the paired continuous values that reveal correlation strength and direction. It is tempting because bar charts communicate category comparisons cleanly, which suits reporting totals by region or channel rather than an advertising spend versus revenue relationship.
- ✗
Remove any outliers from the plot.
Why it's wrong here
Deleting outliers conceals genuine extreme observations and biases the reported correlation. It is tempting because outliers can distort a fitted trend line, so removal is defensible only when values are verified errors, not merely unusual data points that legitimately belong in the analysis.
- ✗
Add a trend line to the scatter plot.
Why it's wrong here
A trend line is optional embellishment; the essential element is reporting the correlation coefficient and its significance so readers judge the strength of the relationship. It tempts because trend lines visually reinforce correlation, but they add no statistical evidence and can imply causation that the scatter plot alone does not support.
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