Given below are two statements : one is labelled as Assertion (A) and the…

Concept

An Assertion–Reason item is settled in two stages. First the truth of each statement is judged independently against its standard definition; only if both statements turn out true does the second stage arise, namely whether the reason actually accounts for the assertion. A statement carrying a universal quantifier — always, never, only, all — becomes false as soon as a single genuine counter-instance exists.

Application

1. Assertion (A) states what data is: information gathered on defined indicators or variables, obtainable either first-hand from the source (primary data — surveys, interviews, observation, experiments) or from already existing records (secondary data — census reports, institutional registers, published datasets). This is the standard research-methodology definition, so (A) is true.

2. Reason (R) claims that data is always collected for the award of a research degree such as MPhil or PhD. Data is routinely gathered for census operations, public-health surveillance, policy planning, market research and journalism, none of which award a degree. One counter-instance is enough to defeat a universal claim, so (R) is false.

3. Because (R) is false, the two statements are not both true, so the second stage — asking whether (R) explains (A) — never arises.

Cross-check

• The truth of (A) rests on what data is, not on why it is gathered. Collecting data for a research degree is one special use of a general activity, not part of its definition.

• Read without the word always, (R) would be a true but partial statement: research degrees are one legitimate purpose among many. As written, the universal quantifier is exactly what breaks it.

• The definition in (A) already allows pre-existing sources, which are typically compiled by governments and institutions for administrative purposes — further evidence that degree work is not the sole occasion for data.

Result:

(A) is correct but (R) is not correct.