Q17 - Advocate: A study of people who had recently

[ohthatpatrick]

Question Type:
Flaw

Stimulus Breakdown:
Conclusion: Taking cold meds is clearly counterproductive.
Evidence: People who took cold meds had more severe symptoms than people who didn't take cold medicine.

Answer Anticipation:
It's a classic Anti-Causal argument. Since we need to argue against the author's conclusion and argue that "taking cold meds IS productive", we have to figure out a different way to interpret the evidence.

How ELSE could we explain why the "people who took cold meds had worse symptoms than those who didn't?"

Well the #1 thought we have when analyzing correlations ("Ppl who are X are more likely to be Y than those who aren't) is "Which came first?" The author is acting like first came the cold meds, next came the worsening symptoms. We could say, "Hey, author, maybe the severe symptoms came first, and that's why these people turned to cold meds". It's not that taking cold meds caused worse symptoms; having worse symptoms caused people to take cold meds.

Correct Answer:
E

Answer Choice Analysis:
(A) Does this match? For this answer to be right, the premise would have to say "most people believe X" and then the conclusion would say "thus, X is true". That doesn't match this argument.

(B) Does this match? I don't think the author treated anyone as an expert, so I'd stop reading there.

(C) Does this match? For this answer to be right, the premise would have to say "in most cases X was true" and then the conclusion would say "thus, in this case X is true". That doesn't match this argument.

(D) Does this match? This refers to the Conditional Logic Flaw (one of the 10 famous flaws). There's no conditional logic in the premise, so it can't be.

(E) YES, the author is thinking that severe symptoms (which are likely the cause of taking cold meds) is an effect of taking cold meds.

Takeaway/Pattern:
"A study found … ppl who are ___ were more likely to be ___ " = CORRELATION.
That's a sign that the author will probably assume some causal story to account for the correlation and our job will be to immediately think, "What's a DIFFERENT way I could interpret the same study / correlaion / puzzling background fact?" With correlations, authors often assume causality is flowing in one direction when it could be flowing in the other direction.

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