Overinterpretation refers to the act of assigning excessive meaning or significance to data, results, or events — going beyond what the evidence actually supports.

### In research or clinical settings, overinterpretation might involve: - Claiming causation when only an association is shown. - Drawing broad conclusions from a small sample or weak data. - Treating a surrogate marker as if it guarantees a clinical outcome (when it’s not validated). - Overstating the relevance of a statistically significant finding that lacks clinical importance.

### Example: If a new drug lowers a biomarker but there’s no proof that it improves survival, and yet the study claims it “saves lives” — that’s overinterpretation.