This is a classic constraint optimization problem that tests inequality manipulation combined with percent calculations. Here's how to work through it systematically.
Key Concept Being Tested: Working backward from constraints to find minimum/maximum values
Step-by-step solution:
1. Set up your variables
Let T = total chips produced. We need to find the minimum number of chips in flagship phones.
2. Parse the constraints
- Less than 0.3% defective → defective chips < 0.003T
- Exactly 5% of defective went to budget → budget chips = 0.05 × (defective)
- More than 60% of non-defective went to flagship → flagship chips > 0.60 × (non-defective)
3. Express flagship chips mathematically
Flagship chips > 0.60 × (T - defective chips)
4. Minimize flagship by maximizing defective
To minimize flagship phones, we want the smallest possible non-defective count. That means maximizing defective chips. The maximum allowed is just under 0.003T.
5. Work with the boundary condition
At the boundary: defective ≈ 0.003T
So non-defective ≈ 0.997T
Flagship > 0.60 × 0.997T = 0.5982T
6. Find the minimum integer value
We need the smallest T where 0.5982T exceeds one of our answer choices. Testing the answers backward from the smallest:
If flagship = 3989, then T = 3989/0.5982 ≈ 6669 chips total.
Common trap: Students often forget that "more than 60%" means strictly greater than, not ≥. This inequality matters for finding the exact minimum.
Takeaway: When you see "less than," "more than," or "at least" in GMAT problems, always work at the boundary conditions to find min/max values—and watch for whether the inequality is strict or inclusive.
Answer: C) 3989