Question: Explain, using the definition of precision, why precision by itself may give an incomplete picture of a model that detects damaged packages in a shipping center.

Sample answer: Precision measures the fraction of packages the model marked as damaged that were truly damaged. A model can achieve a high precision score by being very selective and only flagging the most obvious damage cases. But that does not tell us how many damaged packages the model missed. If many damaged packages are not flagged, the model may still be unsuitable even with strong precision. That is why precision is often considered together with recall.

Key points:

• Precision is the fraction of predicted-damaged packages that are actually damaged
• Precision does not count damaged packages the model failed to flag
• A model can raise precision by making fewer positive predictions
• A complementary metric such as recall is needed to see how many true damaged packages were found

Rubric: Full credit requires defining precision correctly, explaining that it only evaluates the predicted-positive cases, and noting that it ignores missed damaged packages, which is why a second metric such as recall is needed.