This is a classic Data Sufficiency setup. Let me work through whether each statement gets us to a yes/no answer about percent error > 5%.
What we know: 20 participants, three errors of +10, +7, and -2 (or -10, -7, +2). Total error could be 10+7+2 = 19 or 10+7-2 = 15 or other combos depending on direction.
Statement 1: Average of reported scores = 15
If average = 15, then reported total = 20 × 15 = 300.
But we don't know the actual total, so we can't calculate percent error. Not sufficient alone.
Statement 2: Difference between reported and actual total = 15 points
So the error is 15 points. Percent error = (15 / actual total) × 100%.
But without knowing the actual total, we can't determine if this is > 5%.
Actually wait, the errors must sum to 15. So actual total could be 300/0.95 ≈ 316 (if 5% error). Since the error is fixed at 15, and we need to know if 15/actual > 5%, we're stuck without more info. Not sufficient alone.
Together: From (1), reported total = 300. From (2), actual differs by 15. So actual = 285 or 315.
If actual = 315: error % = 15/315 ≈ 4.8% (not > 5%)
If actual = 285: error % = 15/285 ≈ 5.3% (YES > 5%)
Wait, that's two different answers. This means we can't determine a single yes/no. The answer should be E - Statements 1 and 2 together are not sufficient, because the direction of the error matters (whether the reported total is 15 over or 15 under).
Answer: E