Question: Write a concise explanation of why a set of only 10 observed mistakes is too small for dependable error-category estimates, yet can still help a team choose what to work on next.

Sample answer: A sample of 10 observed mistakes is extremely small, so it cannot support reliable estimates of how frequent different error types really are. One or two examples can easily make a category look more important or less important than it truly is. Even so, if the team does not have enough data to gather a larger sample, reviewing those 10 mistakes is still better than guessing blindly. The review can give a rough starting point for deciding what to improve first, as long as the team treats the conclusions as tentative.

Key points:

• Ten mistakes are too few for dependable category estimates.
• Small samples can distort the apparent importance of an error type.
• A larger sample may not always be available.
• Even a small review is better than no review.
• The results can still support cautious next-step planning.

Rubric: A strong response explains that the sample is too small for accurate estimates, notes that small counts can mislead about which errors matter most, and states that the sample can still guide cautious prioritization when no larger sample is available.