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.
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