Introduction / Context:
The statement uses the quantifier “most,” which means “a majority but not all.” Assumption questions often test whether you mistakenly convert a probabilistic or majority claim into an absolute rule. Here we examine two absolute statements to see if the original sentence depends on either of them being true.
Given Data / Assumptions:
- Statement: “Most people who stop smoking gain weight.”
- Assumption I: If anyone stops smoking, they will gain weight (universal claim).
- Assumption II: If one does not stop smoking, one will not gain weight (converse negative claim).
Concept / Approach:
- “Most” does not equal “all,” and it does not imply the converse for the complementary set.
- To be implicit, an assumption must be necessary for the statement to hold.
Step-by-Step Solution:
Assess I: The statement allows exceptions (some quitters may not gain weight). Therefore it does not depend on a universal rule that every quitter will gain weight. I is not necessary.Assess II: The statement makes no claim about people who continue smoking. They may gain or not gain weight for other reasons. II is not necessary.
Verification / Alternative check:
Model with numbers: If out of 100 quitters, 60 gain and 40 do not, the statement “most” is true without either I or II being true.
Why Other Options Are Wrong:
Only I / Only II / Either / Both — all incorrectly convert a “most” statement into absolutes or into an unrelated converse claim.
Common Pitfalls:
Illicit conversion and overgeneralization of statistical statements to universal laws.
Final Answer:
Neither I nor II is implicit
Discussion & Comments