Question: In a concise analytical response, explain why 10 mistakes are insufficient for accurate error-category estimates yet can still inform project prioritization.

Sample answer: An Eyeball dev set with 10 classifier mistakes is very small, so the observed errors provide a weak basis for accurately estimating the impact of different error categories. A few errors can make a category appear more or less important than the limited evidence supports. However, when data is so limited that the team cannot add more examples, examining those 10 mistakes is still better than having no error analysis. The observations can provide a preliminary basis for project prioritization, provided the team treats the category estimates cautiously.

Key points:

• Ten mistakes constitute a very small Eyeball dev set.
• Different error categories cannot be assessed accurately from so few errors.
• Limited data may prevent enlarging the Eyeball dev set.
• The small sample is still better than no error analysis.
• Its findings can help with project prioritization if interpreted cautiously.

Rubric: A strong response identifies the sample as very small, connects that size to inaccurate or uncertain category-impact estimates, and explains why the sample remains useful for cautious prioritization when more data is unavailable.