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vomhorizon
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vomhorizon
Driver: My friends say I will one day have an accident because I drive my sports car recklessly. But I have done some research, and apparently minivans and larger sedans have very low accident rates compared to sports cars. So trading my sports car in for a minivan would lower my risk of having an accident.


The reasoning in the driver’s argument is most
vulnerable to criticism on the grounds that this
argument

(A) infers a cause from a mere correlation

(B) relies on a sample that is too narrow

(C) misinterprets evidence that a result is likely as
evidence that the result is certain

(D) mistakes a condition sufficient for bringing
about a result for a condition necessary for
doing so

(E) relies on a source that is probably not
well-informed


+1 A

I agree with above reasoning...

But i didnt think this much... I felt its just a correlation not a cause....
Because based on research he plans to sell Sports car ...
But there may be other reasons as well need to be considered for accidents...
( moreover accidents depends on driver not on research :lol: )
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Straight A.

Didn't even read the other choices.
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Can someone explain what option D: mistakes a condition sufficient for bringing about a result for a condition necessary for doing so means?
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Bumping for further discussion
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Bunch of incorrect explanations here. C is a good trap that many people fall for. But argument doesn’t say anything about ‘possible’. It just quotes data. So, ‘possible to certainty’ as some have suggested for C is not correct. The driver is doing A. He is not misinterpreting in the way C is worded, he is connecting correlation to causation

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[quote="Chef"]Can someone explain what [u]option D: mistakes a condition sufficient for bringing about a result for a condition necessary for doing so[/u] means?[/quote]

I know it's a bit late for this reply but I will give my two cents here for anybody else wondering about this.

The driver's argument relies on conditional reasoning here without a proper reason for the causation. How? Think about the premise, what if all the people who are reckless drive a sports car and reckless drivers are more likely to end up in a crash, then the sports car driver attribute is completely irrelevant for us to draw any conclusion (it would be neither sufficient nor necessary anymore for the outcome) How would you explain this specific scenario then? This is explainable only by using correlation.

There is a correlation between reckless drivers and drivers who drive a sports car. But causation for the same (that driving a sports car leads to reckless driving) cannot be inferred based on the given information.

Similarly, the minivan and truck drivers may just be safer drivers than sports car drivers.
This choice A is correct in stating that the author considers a correlation as causation.

This question is hard because there is not enough information in the passage to determine whether there is really a causation, and since we need to find the FLAW, we can assume whatever logic the author used here must be wrong, in this case an assumed causation between two events based on statistical evidence that is justifiable by correlation is the flaw

Kudos if this post helps. I have zero kudos at the time when I am writing this answer. :(
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