Logical Reasoning

PT146 · S1 · Q9 In a recent field study of prairie

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In a recent field study of prairie plants, the more plant species a prairie plot had, the more vigorously the plants grew and the better the soil retained nutrients.

Conclusion (Thus)

Having more plant species improves a prairie's ability to support plant life.

Evidence

In a field study, plots with more plant species had more vigorous plant growth and better nutrient retention in the soil.

Evaluate

The evidence is comparative, and the conclusion is causal. When we see that split, we usually think Explain Curious Fact.

The author is trying to figure out why there's such a strong correlation between the number of species and how well the plants grow / how nutrient-rich is the soil. more species || better growth more species || more nutrients in soil

The author interprets this correlation as left causes right: that having more species is causing there to be better growth / more nutrients in the soil.

Whenever we're doing Flaw and see Explain Curious Fact style arguments, we're thinking, .

Whenever author's move from a correlation between X and Y to the idea that X caused Y, we consider the same two alternate explanations: 1. could it be reverse cause? (maybe Y caused X) 2. could it be some third factor? (maybe Z causes both)

In this case, would it make any sense to say that "Growing more vigorously led to more plant species?" or that

Sure! It makes a lot of sense that better soil could lead to more plant species.

It's also possible that there's some 3rd factor explanation, like maybe the plots with more species also had more rainwater / more sunshine / fewer animals that destroy plants, etc.

Goal

Look for an answer complaining that the author went from correlation to causality or pointing out that she's failed to consider some alternate explanation for the data.

9.

The argument is most vulnerable to criticism on the grounds that it

  1. Correct

    infers of two correlated phenomena,

    Why this is right

    Since the answer is structured infers of A that B without considering whether C we want to ask ourselves whether A matches the evidence, B matches a conclusion or assumption, and C matches an objection. The evidence did present two correlated phenomena (really three, but we'll focus on the two that matter): more species || better soil (ability to support plant life) The conclusion did act like X causes Y, that having more species improves the ability to support plant life. And it would be an objection if we said, "Hey author, the greater ability to support plant life is possibly what's causing there to be more plant species". In other words, this answer is presenting the famous Causal Flaw, in which an author overconfidently concludes one possible causal explanation while failing to rule out alternate causal explanations (in this case, Reverse Causality).

    Skill tested: Flaw · how this choice captures the argument's function is the move to repeat next time.

    90% picked this

  2. fails to describe the mechanism

    Bad Objection

    You can produce convincing statistical evidence that "cigarettes increase your risk of lung cancer", even if you don't have a scientific description of how exactly the cigarettes lead to cancer cells. An argument can establish a causal conclusion without spelling out the mechanism that gets us there. Spelling out how more species could improve the fertility of the prairie would definitely add plausibility to the claim that "having more species is causing an improvement in the prairie's fertility", but the argument can't be faulted for having not provided it because it isn't a necessary component of proving that "X causes Y". The language of "how productivity is supposedly increased" is also a curious fit for "increased ability to support plant life". They're almost synonymous, but the former seems more about quantity of plants, while the argument was about growing more vigorously and having richer soil.

    2% picked this

  3. takes for granted that the

    Bad Assumption

    Famous Flaw Bait: Sampling Bad Evidence Match The study compared multiple plots, not one. The author draws on a pattern across plots, so there is no assumption that a single plot speaks for the rest. This describes an assumption the argument does not make.

    4% picked this

  4. bases a general conclusion on

    Sampling

    Famous Flaw Bait: Sampling Bad Evidence Match The conclusion does seem generalized, but who says the data is likely to be unrepresentative? Nothing in the stimulus suggests the plots studied were unusual. We need some footing to say that a sample is sketchy. Samples aren't inherently sketchy.

    3% picked this

  5. takes an increase in number

    Bad Description

    No proportions appear in the argument. The evidence is about the number of species and the vigor of growth / quality of soil, and the conclusion is about ability to support plant life. There is no move from a premise about numbers to a conclusion/assumption about proportion.

    2% picked this

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