Question Type:
Flaw
Stimulus Breakdown:
Conclusion: If you have more galactose than the body can process, it's carcinogenic.
Evidence: There's a correlation between [not having enough enzyme to process galactose] and [cancer].
Answer Anticipation:
This is a correlation to causality argument, for which we're always asking ourselves two questions:
1. Is there some OTHER WAY to explain the background data?
2. Is the AUTHOR'S WAY of explaining it PLAUSIBLE?
So is there some other way to explain why the people WITH the ability to process galactose DON'T have cancer, and the people WITHOUT the ability the process galactose DO have cancer? Or is there some way to shoot down the plausibility of how an overdose of galactose could possibly cause cancer?
Correct Answer:
D
Answer Choice Analysis:
(A) It's too demanding to expect that the diets were the same in ALL other respects. We would like to know if there is some OTHER difference in the two groups that could explain the divergent cancer rate. But this wouldn't be a strong objection, because in the real world we know it would be pretty impossible for a study to maintain IDENTICAL dietary habits for two different groups, for five whole years.
(B) Whether or not the author goes one step farther to make a recommendation is beyond our purview. We're trying to criticize how he arrived at the conclusion, not criticize him for failing to go somewhere else after that.
(C) The author is saying "I think X can cause cancer", not "I think X is the ONLY THING that can cause cancer". So this objection isn't relevant.
(D) YES! Here's an OTHER WAY to explain the background data. If the cancer came first and THEN they lost their ability to process galactose, then obviously the 2nd thing wasn't the cause of the 1st thing.
(E) We don't care whether it was super low or absent entirely. The only salient idea for this argument is that "it was low enough to keep the body from processing galactose".
Takeaway/Pattern: On causal arguments, the most common type of answer is one that deals with some OTHER WAY to explain the background data. The two most common "other ways" are REVERSE CAUSALITY (maybe causality flows in this correlation the opposite way from the way the author was thinking), or SOME THIRD FACTOR (maybe there is some other trait at play here that is *really* the causal factor).
#officialexplanation