A researcher surveys 500 university students at a single campus between 8am and 10am and concludes 'most students prefer morning classes.' What is the primary weakness of this inductive argument?
AThe sample size is too small — 500 students cannot support any generalization
BInductive arguments cannot reach conclusions about preferences, only observable facts
CThe sample is unrepresentative — students present in early-morning locations are self-selected morning people
DThe conclusion should have been stated with certainty, not as a generalization
The limiting factor is representativeness, not size. Surveying people who are already up and active at 8am systematically over-samples students who favor morning schedules. A carefully stratified sample of 100 students across different times and populations could produce much stronger inductive support than 500 from a biased context. Size alone cannot rescue a sampling method that distorts the population.
Question 2 Multiple Choice
A strong inductive argument with all true premises...
AGuarantees its conclusion is true — otherwise it would not count as strong
BMakes its conclusion highly probable but leaves room for it to be false
CIs functionally equivalent to a valid deductive argument with true premises
DEliminates all remaining uncertainty about the conclusion
This is the defining difference between inductive and deductive reasoning. Even a maximally strong inductive argument only makes the conclusion probable — the conclusion could still be false if the world turns out differently than the evidence suggested. Inductive reasoning extends knowledge from observed to unobserved cases; that extension always carries residual risk, which no amount of evidence can fully eliminate.
Question 3 True / False
An inductive argument whose conclusion turns out to be false is necessarily a weak inductive argument.
TTrue
FFalse
Answer: False
Strength is assessed relative to the premises — how probable does the evidence make the conclusion? Even a strong inductive argument (large, representative sample, no counterexamples) can have a false conclusion if the world turns out differently than the evidence suggested. A false conclusion is not evidence of weak reasoning; it may simply reflect bad luck or undiscovered disconfirming evidence.
Question 4 True / False
A larger sample usually produces a stronger inductive argument than a smaller sample.
TTrue
FFalse
Answer: False
Size matters, but representativeness matters more. A large, biased sample can produce weaker support for a universal conclusion than a small, carefully stratified one. The Literary Digest poll of 1936 surveyed millions but predicted the wrong U.S. presidential winner because the sampling method systematically excluded certain demographics. Representativeness is often the binding constraint on inductive strength.
Question 5 Short Answer
Why can a single counterexample defeat even an inductive argument built on a very large sample, and what should a careful reasoner do upon discovering one?
Think about your answer, then reveal below.
Model answer: A counterexample is a direct instance where the generalization fails — it proves the pattern is not universal as stated. Even one well-documented exception means the conclusion must be either narrowed (limiting its scope to exclude the problem case) or abandoned. The careful reasoner investigates whether the exception is explained by special circumstances (preserving the generalization with qualifications) or reveals a genuine flaw in the pattern that requires revising the conclusion.
Inductive reasoning is inherently revisable — discovering exceptions is how generalizations are refined rather than refuted wholesale. The appropriate response is not to dismiss the counterexample but to update the conclusion's scope. This distinguishes strong inductive reasoners from weak ones: the weak reasoner ignores counterexamples; the strong reasoner integrates them.