UGCNET Questions

Deductive reasoning proceeds from the general to the specific. In research, it usually starts with an existing theory or general principle and then derives specific hypotheses that can be tested empirically, allowing researchers to check whether observations support or contradict theoretical expectations.

Option A:
This option correctly describes deduction as starting with a general theoretical framework and narrowing down to specific statements about what should be observed. It reflects the classic sequence used in many quantitative studies.

Option B:
This option illustrates inductive reasoning, where patterns and theories emerge from specific observations; the researcher builds generalizations after examining particular classroom situations.

Option C:
Option C is another example of induction. Generating categories from interview transcripts without prior assumptions involves moving from detailed qualitative data to broader concepts or themes.

Option D:
Option D also reflects an inductive, exploratory approach in which the researcher enters the field without a guiding theory and allows patterns to emerge from the data, rather than deriving specifics from a prior general principle.

Inductive generalisations draw probable, not certain, conclusions from sample data. If the 100 commuters were chosen randomly and the sample reflects the diversity of city commuters, the observed 70% support provides reasonably strong evidence that most commuters prefer the metro. However, sampling error and bias remain possible, so the conclusion is not guaranteed. The cautious phrase “probably reasonable” accurately reflects the strength of this inductive inference.

Option A:
Option A treats the inductive conclusion as certain, ignoring the role of sampling variability and possible bias. Even a good sample cannot guarantee exact population proportions.

Option B:
Option B recognises that a well chosen sample can justify a probable claim about the population while still leaving room for uncertainty. This matches standard statistical reasoning.

Option C:
Option C dismisses all inferences from a sample of 100, which is unjustified; while larger samples are better, 100 can still yield useful information when properly drawn.

Option D:
Option D confuses the target group, since commuters are precisely the relevant population for this question; interviewing them is appropriate, not a flaw.