When 100 people who have not used cocaine are tested for cocaine use, on average only 5 will test positive. By contrast, of every 100 people who have used cocaine 99 will test positive. Thus, when a randomly chosen group of people is tested for cocaine use, the vast majority of those who test positive will be people who have used cocaine.
A reasoning error in the argument is that the argument

(A) attempts to infer a value judgment from purely factual premises
(B) attributes to every member of the population the properties of the average member of the population
(C) fails to take into account what proportion of the population have used cocaine
(D) ignores the fact that some cocaine users do not test positive
(E) advocates testing people for cocaine use when there is no reason to suspect that they have used cocaine.
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When 100 people who have not used cocaine are tested for cocaine use, on average only 5 will test positive. By contrast, of every 100 people who have used cocaine 99 will test positive. Thus, when a randomly chosen group of people is tested for cocaine use, the vast majority of those who test positive will be people who have used cocaine.

A reasoning error in the argument is that the argument

Explanation:
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(A) attempts to infer a value judgment from purely factual premises ---> In that case, it would have strengthen the argument.

(B) attributes to every member of the population the properties of the average member of the population ---> At the most, this option might strengthen the argument. If everyone shares the same property, the conclusion will strengthen. So, discard it.

(C) fails to take into account what proportion of the population have used cocaine
---> This looks fine.

The passage discusses about two groups:
Group 1. One in which, on an average, only 5 test positive
Group 2. Other in which 99 test positive.

Conclusion makes a reasoning error in assuming that even if a randomly chosen group is tested, majority of them will be the ones who have used cocaine i.e., they will belong to group 2. This may not necessarily be true.

What if the majority of the randomly chosen group comprises people belonging to group 1? Though they will still test positive, but they will belong to the group that doesn’t use cocaine. In that case, the argument will become weak.

(D) ignores the fact that some cocaine users do not test positive ---> Irrelevant

(E) advocates testing people for cocaine use when there is no reason to suspect that they have used cocaine. ---> Irrelevant.
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My choice is C.

Hope that helps.


Regards,
Technext
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(A) attempts to infer a value judgment from purely factual premises
-IMO
(B) attributes to every member of the population the properties of the average member of the population
- “properties of average member” is not given.
(C) fails to take into account what proportion of the population have used cocaine
- Do we really need to know “proportion” of people who took cocaine? This is a study result and mostly concluded the result from factual premises.
(D) ignores the fact that some cocaine users do not test positive
- Never ignored such case. 1% is negative
(E) advocates testing people for cocaine use when there is no reason to suspect that they have used cocaine.
- “Reason of suspect” is OOS
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Now only option E is left.

Any takers?
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I've seen a few similar questions about 'false positives' and 'false negatives'. You can imagine the following situation:

100 people in Country X use cocaine
1,000,000 people in Country X do not use cocaine

Test all of these people, and 99 of the 100 cocaine users will test positive, while 50,000 of the non-users will test positive. You have 50,099 people in total who test positive, but of those, only 99/50,099 ~ 0.2 % are actually cocaine users.

Without knowing something about cocaine use in the population as a whole, we can't say very much about the people who will test positive. C is certainly the answer.
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Nice question. C it is ..