Critical Reasoning

An argument gives reasons for a conclusion. Check whether the reasons really support what is claimed.

Reduce the argument to evidence therefore conclusion. Find the missing link, then test choices against that link rather than their general plausibility.

“All library members have cards. Isha has a card. Therefore Isha is a library member.” Is the conclusion certain? 1. Members having cards does not mean only members have cards. 2. Isha might have a different kind of card. 3. The conclusion is not guaranteed by the given reason.

The library-member region sits inside the cardholder region, matching the premise. Isha can be in the larger region outside membership without contradicting that premise. This counterexample shows why the conclusion is not certain. The dot represents a possible position, rather than a claim about Isha’s actual membership.

A factory installs new software; defects fall from 8% to 4%. Management credits the software. During the same period it also changed to a supplier with better materials. This weakens the causal attribution because another change can explain the drop. It does not prove that software had no effect. A stronger evaluation compares similar production lines with and without the software while controlling materials.

Do not reverse a one-way rule unless the passage allows it. Necessary assumptions need not make the conclusion certain. Avoid selecting a stronger, sufficient assumption when a necessary one is requested.

A strengthening fact makes the conclusion more credible; a weakening fact makes it less credible. Neither must prove the conclusion true or false.

An advert is credited with higher sales. Finding that sales rose equally in regions without the advert weakens the causal claim. Finding a rise only in comparable advertised regions strengthens it.

A useful evaluation question has answers that push the argument in different directions. Ask why both yes and no would matter.

A school claims tablets improved scores. Asking whether the test difficulty stayed the same is useful: an easier test could explain the gain, while equal difficulty removes that explanation.

A paradox question asks for a fact that makes two apparently conflicting observations compatible. Accept both observations as true.

A shop cuts prices but total revenue rises. If the lower prices increase the number of items sold enough, revenue can rise. The explanation does not deny the price cut.

Reduce the argument to evidence therefore conclusion. Find the missing link, then test choices against that link rather than their general plausibility.

A factory installs new software; defects fall from 8% to 4%. Management credits the software. During the same period it also changed to a supplier with better materials. This weakens the causal attribution because another change can explain the drop. It does not prove that software had no effect. A stronger evaluation compares similar production lines with and without the software while controlling materials.

Necessary assumptions need not make the conclusion certain. Avoid selecting a stronger, sufficient assumption when a necessary one is requested.