DA0-002 Visualization and Reporting Practice Question
A heat map of store sales by region shows very low correlation between advertising spend and revenue, but a scatter plot of the same data shows a strong positive relationship. What is the most likely cause?
⚠ Common exam trap
DA0-002 often tests the confusion between visual encoding problems (color scale) and data transformation problems (aggregation) — candidates must recognize that aggregation, not chart aesthetics, is what distorts correlation.
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
✓
Data was aggregated incorrectly in the heat map
A heat map that shows low correlation while a scatter plot of the same data shows a strong positive relationship most likely indicates the heat map aggregated the data incorrectly — for example, summing or averaging across regions in a way that masked the underlying per-store relationship. Aggregation can distort or reverse apparent correlations (a form of Simpson's paradox), so the heat map's aggregated view is misleading. The scatter plot at the raw data level reveals the true relationship.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Data was aggregated incorrectly in the heat map
Why this is correct
Aggregating data into regional totals collapses the underlying variation, obscuring the strong positive relationship visible at finer granularity. The heat map's coarse aggregation masks the correlation that the scatter plot reveals at individual data points.
- ✗
The heat map used an incorrect color scale
Why it's wrong here
A wrong colour scale would misrepresent magnitude visually but would not alter the computed correlation coefficient underlying the heat map. It tempts because colour mapping errors are a common dashboard fault, and reversing a scale can invert apparent patterns — but correlation is calculated from data values, independent of palette.
- ✗
Outliers were removed only for the scatter plot
Why it's wrong here
Removing outliers from only one chart would typically weaken, not strengthen, the scatter plot's apparent correlation, and it does not explain a heat map showing near-zero correlation. It tempts because outliers genuinely distort correlation coefficients, making selective removal a plausible-sounding cause — but the real issue is aggregation hiding within-region variation.
- ✗
The chart types are inherently incompatible
Why it's wrong here
Heat maps encode a single aggregated value per region, so they cannot display the per-observation pairing that a scatter plot reveals; the apparent weak correlation is an artefact of aggregation, not of chart incompatibility. Chart types are not inherently incompatible — both render the same data. A heat map is correct when showing density or a matrix of two categorical dimensions.
Go deeper
Related to this question
About these practice questions
Courseiva writes every DA0-002 question from scratch — 1,004 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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
This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.