The argument's conclusion focuses narrowly on the age at which people experience their first heart attack, so the severity of those heart attacks is outside the scope of that conclusion.

I had a gripe with (A), though – what if tons of nonsmokers have deadly heart attacks at early ages (pre-62) for some reason? That is, what if nonsmokers tend to have way more severe heart attacks than smokers do -- so much more severe that they tend not to survive their first heart attack?

To address this gripe we need to lean on the sufficient assumption implications of the stem (discussed in the analysis). Even if the stimulus included information addressing this potential problem with the argument, the conclusion would still be incorrectly drawn because of the unrepresentative sample problem.

The argument's conclusion focuses narrowly on the age at which people experience their first heart attack – medical treatments received afterward have no impact on that.

The argument's conclusion focuses narrowly on the age at which people experience their first heart attack – information about second heart attacks is irrelevant to that claim.

The argument's conclusion is about tendencies across the data set. It doesn't say "every nonsmoker has their first heart attack 11 years after every smoker." The value of individual data points doesn't affect the overall trend.

I had a gripe with (D), though, because medians can mask weird data distributions. What if the earliest age a smoker had their first heart attack was 50? That is, what if the data sets looked like this:

Smokers: 50, 50, 50, 50 … 51 (median) … 55, 59, 63, 68
--------
Nonsmokers: 45, 51, 55, 60 … 62 (median) … 63, 64, 66, 69

In this case, the median ages are still 51 and 62, but it would be misleading or even incorrect to say nonsmokers tend to have their first heart attack eleven years later than smokers.

To address this gripe we need to lean on the sufficient assumption implications of the stem (discussed in the analysis). Even if the stimulus included information addressing this potential problem with the argument, the conclusion would still be incorrectly drawn because of the unrepresentative sample problem.

This argument draws a conclusion about everyone from data about people who survived their first heart attack. That sample is unrepresentative. (E) correctly points to the missing group of people we need information about. [Everyone] = [people who survived] + [people who didn't survive].