NCA-GENL Data Analysis and Visualization Practice Question
A data scientist has a table of 500 LLM evaluation runs, each with a numerical faithfulness score from 0 to 1 and a categorical model version label. They want a compact view comparing the score distributions across model versions, including medians and spread, in a single figure. Which visualization should they choose?
⚠ Common exam trap
The trap here is choosing a plot that shows individual points or relationships, when the requirement is grouped summary statistics such as median and spread in one compact figure.
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
✓
A grouped box plot of faithfulness score by model version.
When comparing a continuous score across categorical groups, box plots are the standard compact choice because each box summarizes median, interquartile range, and outliers per group. They allow immediate side-by-side comparison of both center and spread across model versions, which is precisely what the data scientist needs in a single figure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A grouped box plot of faithfulness score by model version.
Why this is correct
Box plots place each model version side by side and display median, quartiles, and outliers for its score distribution. This provides both central tendency and spread in one compact figure, directly matching the comparison goal for categorical groups.
- ✗
A network graph connecting runs that share the same model version.
Why it's wrong here
A network graph encodes relationships, not distributions. It provides no direct read of median or spread per version, and the resulting structure would be dominated by the shared label rather than score behavior, making it unsuitable for this comparison.
- ✗
A heatmap of faithfulness score binned by run index and model version.
Why it's wrong here
A heatmap can encode density, but with 500 runs and a continuous score it becomes visually noisy and does not directly display medians or quartiles. Extracting spread comparisons across versions from color intensity is imprecise and slower than a purpose-built distribution plot.
- ✗
A single scatter plot of faithfulness score against run index.
Why it's wrong here
Plotting score against run index shows ordering but not grouped distributions. Comparing medians and spread across model versions would require manually separating the points, and overlapping versions would be hard to distinguish, so it is not the compact comparison view requested.
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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 NVIDIA exam blueprint
This NCA-GENL practice question is part of Courseiva's free NVIDIA 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 NCA-GENL exam.