PT64.S1.Q22 - Microbiologist: Because heavy metals are normally

BlindReviewer

Hi all,

I was hoping someone might be able to help me with two things here:

1) In my BR I was really torn between A and B and eventually chose A. But when I found out it was B, I realized that I had totally paraphrased the argument rather than reading it exactly. I was thinking the causation was "resistance to heavy metals" causes "resistance to antibiotics." So I ruled out B because it didn't really show any relationship between the resistances. But now I see that the causation is actually between "exposure to heavy metals" causes "resistance to antibiotics." The really strange thing for me here is the way the stimulus kind of lays it out like this, with an implied correlation:

[Exposure to heavy metals (correlated with heavy metal poisoning resistance)] presumably causes/correlated with [resistance to antibiotics].

Is that part about resistance to heavy metal poisoning just fluff in cases like this (i.e. does the implied correlation not matter)? I've just never seen it before and was curious what the theory is here.

2) This question did bring to mind that the correlation between the absence of a supposed cause with the absence of a supposed effect strengthens a causation argument. Originally, I was only thinking about reverse causation and a third independent cause, but I was wondering what else there is I should know about causation theory (briefly skimmed the causation section of the curriculum but will go back in detail) that tends to come up and is a bit more nuanced/something tricky to watch out for.

Thanks!

Admin note: edited title
https://7sage.com/lsat_explanations/lsat-64-section-1-question-22/

M.Yanka106

I find it hard to pin down the structure of an argument when I read it exactly. I think paraphrasing is a good idea just circle all modifiers or get a clear idea of what is causing what.

Structure- the argument is noting 2 things about a certain bacteria; A (exposure to heavy metal) and B (resistance to antibiotics). We have to strengthen the idea that A promoted B.

At first, like you, I also paraphrased the argument as resistance to HM promoted resistance to antibiotics. I was also between A and B. Even if you did all of that, Ans B is still better. Ans A says that bacteria that are not resistant to antibiotics are not resistant to HM poisoning. I eliminated A because the order of the relation is reversed (don't you think?). We are trying to strengthen the idea that HM promoted resistance to antibiotics. If you examine bacteria that are NOT resistant to antibiotics, what good will it do? Answer B in effect is saying that when the cause was absent the effect was also absent, strengthening the cause effect relation. Bacteria living in HM free environment show no resistance to antibiotics.

As a disclaimer, I struggle with the causation-correlation idea too. It is so intertwined with the cause-effect idea making it hard to tell which direction to take. In addition to the 3 common rules to strengthen/weaken argument about causation-correlation, it will be a good idea to keep the rules regarding strengthening/weakening cause-effect argument in your bag of tricks.

Examine PT45 first section of LR Que no.12 (reproductive abnormalities in fish). It is a very difficult weakening question. I think the structure of Que12 is very similar to 64-sec1-22.

BlindReviewer

Thanks for your response!

During BR it did cross my mind that the "most" argument seemed reversed. But I thought that it would still strengthen the argument because it shows a relationship between the two types of resistances.

I messed around a bit with two ideas to help clarify this for me (and hopefully this will help others):

1) If we think in terms of conditional statements, the most statement gives us:

If you are not resistant to antibiotics -> likely that you are not resistant to heavy metals.

You would be committing a grave reasoning flaw if you were to say that this statement is the same as saying that if you are resistant to heavy metals you are likely to be resistant to antibiotics. "Most" statements don't go backwards! That would be the same as saying A most B = /B most /A

2) If you try putting numbers to it, you see that the information in A doesn't really help us that much because it doesn't tell us what the actual breakdown is of bacteria who are resistant/not resistant to either heavy metals or antibiotics. All this tells us is a characteristic of a subset: those that are not resistant to antibiotics.

If we say there are 1000 bacteria in the world, we can see how loosely the "most" statement helps the correlation.

In one way, we COULD strengthen the correlation. For example, if 400 were RA (resistant to antibiotics) and 600 NRA (not resistant to antibiotics), then we would have to say something like 500 are NRH. Consequently, 500 would be RH. This shows a pretty good overlap of RA and RH (400/500).

But using the same "most" statement, we could WEAKEN the correlation. For example, if 300 were RA and 700 were NRA, we would have to say something like 400 are NRH and 600 are RH. But this overlap of RH and RA is only 600/300, not nearly as strong.

The fact that this kind of most statement doesn't specify the distribution of the entire set of bacteria is the theoretical background behind why it doesn't work (I think).

Thanks for the reference to the other question as well, will definitely check it out. And if someone else could weigh in on these "most" statements and why we can't flip them/relation to causation, that would be really helpful!