UGC NET Questions (Paper – 1)

A strong analogical argument highlights similarities that are relevant to the property being inferred rather than piling up many trivial or unrelated likenesses. The more closely the cited similarities are connected to the conclusion, the stronger the analogy. It does not require the cases to be identical, but it does require that relevant respects be shared in a way that supports the projected claim.

Option A:
Option A relies on superficial similarities, which may look impressive but do not actually support the specific conclusion, weakening the analogy.

Option B:
Option B focuses on relevance and connection to the conclusion, which is the hallmark of a persuasive analogical inference.

Option C:
Option C demands total identity, which is rarely achievable and is not necessary for analogical reasoning; analogy works precisely because the cases are not identical.

Option D:
Option D suggests that a good analogy can never be challenged, which is incorrect; analogical arguments remain defeasible and open to counterexamples.

Analogical reasoning draws a conclusion about one domain by comparing it to another domain that is better understood. In the brain–computer example, we use the known structure and function of computers as an analogy to reason about how the brain might work. The inference depends on perceived similarities rather than strict deductive necessity. This is a classic case of analogical reasoning used in science and philosophy.

Option A:
Option A explicitly sets up a comparison and then transfers insights from the analogue (computer) to the target (brain), which is the essence of argument by analogy.

Option B:
Option B is a deductive argument using class inclusion and does not rely on similarity between different domains.

Option C:
Option C is a standard conditional inference, “if p then q; p, so q,” which exemplifies deduction, not analogy.

Option D:
Option D simply states a definition without comparing it to anything else, so no analogical structure is present.