Researchers recently studied the relationship between diet and mood, using a diverse sample of 1,000 adults. It was f...

shunhe on August 11, 2020

Hi @ruchitaj,

Thanks for the question! So to briefly summarize the argument: these researchers found a correlation between eating chocolate and feeling depressed, with more chocolate correlating with being more depressed. And then it makes a causal conclusion based on this correlative evidence, that by reducing excessive chocolate consumption, adults can improve their mood (the idea underlying this that it’s the excessive chocolate consumption that’s causing the decrease in mood). So here, we clearly have a classic correlation vs. causation confusion.

Now we’re asked for the flaw in the argument. (C) sums up exactly what we said above, that the argument confuses correlation with causation. The conclusion thinks chocolate causes depression because more chocolate is correlated with more depression.

(A), on the other hand, is a bit different: it tells us that the argument improperly infers from the fact that a substance causally contributes to a condition that reduction in the consumption of the substance is likely to eliminate that condition. In other words, this flaw occurs when the argument thinks that reducing a cause will completely get rid of the effect. But that’s not what’s going on here! First of all, as we discussed, the evidence isn’t causal, so we can’t say that there’s even a “fact that a substance causally contributes to a condition.” Because again, the evidence shows correlation, not causation. And second, does the argument say eating less chocolate will completely cure your depression? No, it just says that you can feel better by eating less chocolate. So it doesn’t argue that “a reduction in the consumption of the substance is likely to eliminate that condition.” That’s what separates (A) from (D) and makes it wrong.

Hope this helps! Feel free to ask any other questions that you might have.