Key concept: Data Sufficiency "maximize/minimize" — with a bounded inequality, you need to show whether every possible scenario gives the same yes/no answer.
The common trap: Students see "median = 120" in Statement 1 and assume Irene is somewhere near 120. But the median only pins down the middle value in the sorted list — Irene could be the heaviest member, far above 120.
Setup: 5 members, each ≥ 100 lbs, average = 117 → total = 585 lbs. Question: Is Irene < 150?
Step 1 — Statement 1: Median = 120.
Sort the five weights: w1 ≤ w2 ≤ w3 ≤ w4 ≤ w5. So w3 = 120.
To find the maximum Irene could weigh, minimize everyone else's contribution:
Set w1 = w2 = 100 (minimum allowed), w3 = 120 (fixed), w4 = 120 (minimum ≥ median).
Then: 100 + 100 + 120 + 120 + Irene = 585 → Irene = 145.
Even at the absolute maximum, Irene = 145 < 150. The answer is always YES.
→ Statement 1 alone is Sufficient.
Step 2 — Statement 2: Irene = Tina + 5.
Again, minimize the other three: set them all to 100.
100 + 100 + 100 + T + (T + 5) = 585 → 2T = 280 → T = 140, Irene = 145 < 150.
Can the other three weigh more, pushing Irene down? Yes — that would only make Irene lighter. And the floor is Irene ≥ 105 (since Tina ≥ 100). So Irene is always between 105 and 145 — always less than 150. Answer is always YES.
→ Statement 2 alone is Sufficient.
Answer: D — each statement alone is sufficient.
Takeaway: In yes/no DS problems with an inequality, the key question is always "what's the maximum (or minimum) the unknown can be?" If even the worst case still answers YES, the statement is sufficient.