NCA-GENL Data Analysis and Visualization Practice Question
A team is evaluating a retrieval-augmented generation pipeline. They have a dataset of 500 queries, each with a retrieved context and a generated answer. The goal is to visualize how often the generated answer is faithful to the retrieved context versus hallucinated, and to compare this across three different retriever configurations. Which visualization best supports this comparison?
⚠ Common exam trap
The trap here is choosing a pie chart because it shows proportions, but a single pie chart cannot compare proportions across multiple retriever configurations.
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 bar chart showing the proportion of faithful, partially faithful, and hallucinated answers for each retriever configuration.
The task requires comparing categorical faithfulness outcomes across three retriever configurations. A grouped bar chart places the proportions of each faithfulness category side by side for each configuration, making differences immediately visible. The other options either collapse the comparison, use continuous variables that do not represent faithfulness, or focus on a single example.
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 bar chart showing the proportion of faithful, partially faithful, and hallucinated answers for each retriever configuration.
Why this is correct
A grouped bar chart compares categorical proportions across multiple configurations side by side. Faithfulness categories are discrete, and the three retriever configurations form natural groups. This directly answers how often answers are faithful versus hallucinated and allows an at-a-glance comparison across retrievers, which is exactly what the team needs.
- ✗
A pie chart showing the overall proportion of faithful, partially faithful, and hallucinated answers across all retrievers combined.
Why it's wrong here
A pie chart of the combined data collapses all three retriever configurations into one, eliminating the comparison the team needs. It shows overall proportions but cannot reveal differences between retrievers. Since the goal is to compare configurations, a single pie chart is insufficient and misleading for that purpose.
- ✗
A heatmap of token-level attention weights between the generated answer and the retrieved context for a single query.
Why it's wrong here
A heatmap of attention weights for one query is a qualitative, single-example visualization. It does not aggregate across 500 queries or compare retriever configurations. While useful for debugging a specific case, it cannot show how often answers are faithful versus hallucinated across the dataset, so it fails the stated goal.
- ✗
A scatter plot of answer length versus retrieval score, colored by retriever configuration.
Why it's wrong here
A scatter plot of length versus retrieval score shows correlation between two continuous variables, not the frequency of faithfulness categories. Coloring by retriever may reveal clusters, but it does not quantify the proportion of faithful or hallucinated answers. It fails to directly answer the comparison of faithfulness rates across configurations.
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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
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