DA0-002 Visualization and Reporting Practice Question
An analyst creates a histogram of customer transaction amounts but observes that the distribution looks bimodal. Upon review, the analyst realizes that two different customer segments (retail and wholesale) were combined. Which action best addresses this?
⚠ Common exam trap
The trap is thinking that a single visualization with colors or more bins can solve the issue, but the root cause is mixing two populations; the best practice is to disaggregate.
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
✓
Create two separate histograms, one for each segment
Creating two separate histograms, one for each customer segment (retail and wholesale), best addresses the bimodal distribution because it allows the analyst to see the underlying distributions of each segment clearly. Combining them into one histogram obscures the distinct patterns, while separating them reveals the true characteristics of each group. This is a fundamental principle of data visualization: when data contains subgroups, disaggregating can provide more meaningful insights.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create two separate histograms, one for each segment
Why this is correct
The bimodality is an artefact of mixing two populations with different spending patterns. Splitting retail and wholesale into separate histograms removes the confounding grouping variable, revealing each segment's true unimodal distribution instead of one misleading combined shape.
- ✗
Use a single histogram with two colors for segments
Why it's wrong here
Colouring one histogram by segment still overlays both populations on shared bins, so the bimodal shape remains and the modes stay entangled. Colour coding suits highlighting categories within a single distribution, not separating two distinct underlying populations.
- ✗
Use a box plot instead of a histogram
Why it's wrong here
A box plot summarises median, quartiles and outliers but collapses the distribution's shape, so it cannot separate the two underlying modes. It suits comparing spread across groups, not resolving bimodality caused by combining retail and wholesale segments.
- ✗
Increase the number of bins to see more detail
Why it's wrong here
Adding bins refines resolution but cannot remove bimodality, because the two segments genuinely occupy different transaction ranges. More bins suit detecting finer structure within one population, not disentangling two mixed populations that should be plotted separately.
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.