DA0-002 Visualization and Reporting Practice Question
You are a data analyst for a logistics company. The company has a fleet of delivery trucks and tracks performance metrics including delivery time, fuel consumption, and distance traveled. Management wants a dashboard to monitor driver efficiency and identify underperforming drivers. You have access to a dataset with columns: DriverID, Date, RouteID, Distance (miles), FuelUsed (gallons), DeliveryTime (minutes). The dataset contains 10,000 records from the past year. You need to create a visualization that allows management to quickly compare the average fuel efficiency (miles per gallon) of drivers and also see how consistent each driver's efficiency is. Which of the following approaches is the best course of action?
⚠ Common exam trap
Candidates often choose a bar chart (Option D) because it shows averages, but they overlook the requirement to also see consistency, which only a box plot or violin plot can provide in a single visualization.
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 a box plot grouped by DriverID showing the distribution of MPG for each driver.
A box plot grouped by DriverID is the best choice because it simultaneously shows the central tendency (median MPG) and the spread (interquartile range and outliers) of each driver's fuel efficiency. This allows management to quickly compare average efficiency across drivers while also assessing consistency—drivers with narrow boxes are more consistent, while those with wide boxes or many outliers are erratic. The other options either fail to show distribution (bar chart, line chart) or require manual interpretation of consistency (scatter plot).
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 a line chart with Date on the x-axis and MPG on the y-axis, with separate lines for each driver.
Why it's wrong here
Plotting daily MPG per driver over a year yields 10,000 overlapping points, obscuring both average comparison and consistency. Line charts suit continuous trends over time for few series, not ranking many drivers by mean and spread.
- ✓
Create a box plot grouped by DriverID showing the distribution of MPG for each driver.
Why this is correct
A box plot grouped by DriverID shows each driver's MPG distribution, so management compares median efficiency and sees spread or outliers indicating consistency. This satisfies both requirements — average comparison and consistency — in one compact visual, unlike single-value summaries.
- ✗
Create a scatter plot with Distance on the x-axis and FuelUsed on the y-axis, color-coded by DriverID.
Why it's wrong here
Distance versus FuelUsed plots raw consumption, not the derived MPG ratio, and colour-coding by DriverID mixes drivers into one cloud, preventing per-driver average and consistency comparison. Scatter plots suit correlation between two continuous variables, not grouped distribution summaries.
- ✗
Create a bar chart showing the average MPG for each driver.
Why it's wrong here
A bar chart of average MPG compares central tendency only, discarding the consistency requirement; variance across the year is invisible. Bar charts suit ranking single summary values, whereas showing both mean and spread per driver needs a distribution view such as box plots.
Go deeper
Related to this question
About these practice questions
This DA0-002 question is part of Courseiva's 1,004-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.