Another stellar explanation!
To the original poster, I see what you mean about your scenario - basically, can't we manipulate the numbers so that (A) doesn't strengthen? Yes, we could, but we'd also have to interpret "alarming" as being a relatively small number. And, notice how much work you have to do to make (A) not strengthen. I think you should step back and look at it a bit more plainly:
The conclusion is that we can expect some health issues. Why? Because gas with MBTE will be available soon, and we see an alarming number of illnesses among folks that work with MBTE.
What's the gap? Well, maybe those folks are getting sick from something other than the MBTE. It's not hard to imagine that working at an oil-refinery might carry some other health risks!
What we see in the answer choices is that the wrong ones strengthen the relationship between MBTE and illness. What we see in the correct answer, (B), is that these illnesses can also show up from other causes (conditions). But since that data is quite broad in that we don't know how often folks get sick from these other causes and in that we don't know how the oil-refinery folks fit in (are they getting these other conditions?), (B) ends up being just a random fact.
Let me lean on Tim for the wrong answer explanations:
timmydoeslsat Wrote:
A) This strengthens the idea of MBTE being the cause. You can strengthen a cause and effect argument by:
Cause not present - Effect not present
Cause is present - Effect is present
This answer shows that when MBTE is not present, the effect is not present.
Yes, the answer isn't as strong as it could be since it only says that "most" of these workers don't get sick from MBTE, but it does help address the concern that perhaps oil-refinery workers are getting sick from something else. (A) gives us some data that indicates otherwise.
B) This does not strengthen the idea that MBTE is the cause. This tells us that the symptoms listed from the stimulus could have been derived from other medical conditions. This is our answer.
C) This shows when the cause was present, so was the effect.
D) This shows cause and effect with the MBTE juxtaposed to regions without the cause, and those regions did not have the effect.
E) This is a classic argument booster that tells us the sample from the survey is representative.