woohoo921
I realize that this question is discussed at nauseum. However, based on
the Official Guide's explanation for this question, I am still confused as to why Choice C is incorrect based on the pre-thinking examples mentioned by
the Official Guide.
The Official Guide says, "several factors other than greater experience and caution could explain the lower accident rate among the older drivers...." and provides several reasons below:
1.) "or perhaps the older drivers are more often retired, their schedules less often lead them to drive at times of day when accident rates are greater for everyone"
2.) "or they might be more likely to live in rural areas with less traffic and lower accident rates"
The
OG then says choice C is incorrect because "even if drivers 65 and older are just as likely as younger drivers to drive in inclement weather, they may do so far more carefully than the younger drivers, so the holder drivers' greater experience and caution could still explain their lower accident rates." I understand how the
OG can negate this argument, but the GMAT's other possible reasons mentioned in its "reasoning" section above can also be negated using this same reasoning in that:
1.) even if drivers 65 and older are just as likely as younger drivers to drive at times of day when accident rates are greater for everyone, they may do so far more carefully than the younger drivers, so the holder drivers' greater experience and caution could still explain their lower accident rates
2.) even if drivers 65 and older are just as likely as younger drivers to live in rural areas with less traffic and lower accident rates, they may still drive far more carefully than the younger drivers, so the holder drivers' greater experience and caution could still explain their lower accident rates.
I have seen it mentioned on the GMATCLUB that you shouldn't really rely on
the Official Guide's explanation, but they seem to undermine their pre-thinking examples based on how they justify why choice C is incorrect.
Look at (C) again. (C) is quite different from (A) because (C) does not include "not."
As a result (C) is a weakener. After all, rather state the assumption that there is NOT an alternative cause of the lower accident rates, (C) PRESENTS an alternative cause, which is basically that older drivers don't drive in bad weather. By presenting an alternative cause, (C) weakens the case for believing that the greater experience and developed habits of caution possessed by drivers in the 65-and-older are the causes.
These two, which are based on what you mentioned, are also weakeners.
1.) the older drivers are more often retired, their schedules less often lead them to drive at times of day when accident rates are greater for everyone
2.) the older drivers are more likely to live in rural areas with less traffic and lower accident rates
A necessary assumption is (C) or one of those two + NOT.
So, your analysis is spot on, you just missed that all of them, including (C) would be assumptions with the addition of NOT. So, because they don't include NOT, none of them are assumptions that the argument relies on.
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Another question: To confirm, Choice A is the best answer because you can only really make this argument more foolproof if you are using similar mileage as a fair comparison.
Well, the mileage does not have to be similar, but the miles driven by the older drivers can't be very many fewer. After all, if the miles driver by older drivers are very many fewer, then that lower mileage could be the cause of the lower accident rates.
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Would it be the case that similar sample sizes were used in forming these statistics as another assumption that the argument depends upon? For example, it would not necessarily make sense to compare two people in 65+ group to 1,000 people in the 21 & under group to 10,000 people in the 21-24 age group.
The sample sizes do not have to be similar. Of course, a sample size of 2 would be too small to effectively support an argument about accident rates, but the argument would work just fine if the sample sizes were, for example, 1000, 10,000, and 20,000. After all, the argument is about accident rates. The sample size would not affect the accident rate as long as the sample size is not simply too small to support any argument about accident rates.