What should a good answer change?
GMAC lists strengthening and weakening among Critical Reasoning tasks. Treat the information in each answer choice as true and assess its effect on the argument. The task is not to choose the most interesting statement or check whether it is true in real life.
For a causal conclusion, isolate the proposed cause and observed effect. Then look for what makes their relationship more or less credible: a relevant comparison, a competing factor, a change in measurement, or a reversed relationship. These are Upsilar reading tools, not an automatic answer list.
Does the new system explain the drop in errors?
Fictional case — Upsilar. A warehouse introduced barcode checks in April. Its recorded packing error rate fell from 12 errors per thousand orders in March to 6 per thousand in April. The manager concludes that the barcode checks reduced packing errors.
The fact is a drop in the recorded rate. The conclusion attributes that drop to barcode checks. It is not about the system’s popularity or profitability. Information on either topic may be off target.
Which additional information most strengthens the manager’s conclusion?
Choose an answer.
The solution, step by step
B.
The method in action
- The comparable site that kept its old method did not see a decline. This comparison makes an explanation common to both sites during the period less plausible.
- This does not prove that every other factor is identical or establish certain causation. Still, it supports the link more than the other choices.
- A and C give an appearance or preference; D describes a habit with no stated effect on the comparison; E describes a separate plan. None links the decrease to the checks.
Which additional information most weakens the same conclusion?
Choose an answer.
The solution, step by step
C.
The method in action
- The measurement changed at the time of the decline: April’s rate excludes errors that were counted in March. The recorded decline may therefore occur without a comparable decline in actual errors.
- C does not prove the system is useless. It weakens the evidence used to conclude that the system reduced errors.
- A describes a useful capability without showing its actual effect; B, D, and E do not explain the measured difference.
The pitfall
Weakening evidence does not prove the opposite conclusion
After learning C, you cannot claim that barcode checks increase errors. You only know that the rate comparison no longer establishes their effectiveness as well. Confusing criticism of the evidence with proof of the opposite can lead you to choose an overstated answer.
Likewise, a strengthening answer does not have to eliminate all uncertainty. Demanding a perfect experiment may lead you to reject the choice that genuinely improves the argument among those offered.
How can you keep the question in mind through the final choice?
Write a short arrow: barcode checks → fewer errors. Above it, note what the question asks: strengthen or weaken. For each choice, explain its effect in one conditional sentence. If it were true, would the arrow be better supported, less supported, or unchanged?
When reviewing your work, compare distractors with the exact conclusion. Information about costs might matter if the conclusion concerned profit; it is not relevant here just because it mentions the same warehouse. The logical relationship defines what matters, not the setting.
Then revisit the argument with a different conclusion and see which information changes its role. This exercise builds reading precision without teaching trigger words that supposedly produce the answer automatically.
Key takeaways
- Identify the relationship being tested, not just the topic of the passage.
- A good answer affects that relationship.
- Weakening does not require proving the opposite.