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
A line chart with many drivers would be too cluttered and does not efficiently compare distributions.
- ✓
Create a box plot grouped by DriverID showing the distribution of MPG for each driver.
Why this is correct
A box plot shows median, quartiles, and outliers, allowing comparison of both central tendency and variability.
- ✗
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
A scatter plot with 10,000 points would be cluttered and not clearly show per-driver efficiency or consistency.
- ✗
Create a bar chart showing the average MPG for each driver.
Why it's wrong here
A bar chart shows only averages, not variability; it does not indicate consistency.
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Written by Johnson Ajibi, MSc IT Security
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