Logical Reasoning

PT12 · S4 · Q23 Insurance industry statistics demonstrate that

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Insurance industry statistics demonstrate that cars with alarms or other antitheft devices are more likely to be stolen or broken into than cars without such devices or alarms.

Conclusion (Therefore)

Antitheft devices do not protect cars against thieves.

Evidence

Cars with antitheft devices are more liekly to be stolen or broken into than cars without antitheft devices.

Evaluate

This is a Parallel Flaw question so the first order of business is to name that flaw. This argument has one of the Famous Flaws, so if you see that, you're ready to go to the answers. If you can't name that flaw yet, try the Anti-Conclusion test. Given that the Evidence is true, how could you argue that the Conclusion is false? If cars with the devices are more likely to be jacked or broken into, how could you argue that the devices are actually protective? Maybe without those devices, even MORE of them would be getting jacked/robbed? This is the classic objection to what we call Anti-Causal arguments: arguments that claim something isn't having a particular effect. The most common flavor of Anti-Causal argument concludes a plan isn't working because the problem persists. When you see that flavor of argument, you should always think

The other noteworthy aspect of this argument, and what makes it a Famous Flaw, is that the two samples we're comparing are meaningfully different in a way the argument overlooks. Perhaps theives are more interested in jacking cars with the devices because those cars tend to be newer/fancier than cars without them.

Goal

Look for an answer that overlooks a meaningful difference between two samples and concludes that one thing doesn't cause another.

23.

The pattern of flawed reasoning in the argument above is most similar to that in which one of the following?

  1. Since surveys reveal that communities

    Bad Match

    The evidence in the original argument isn't about averaging things. The conclusion in the original argument isn't that two things are typically correlated.

    4% picked this

  2. Most public libraries are obviously

    Bad Match

    The evidence in the original argument doesn't have the structure "Most X's have Ys but not Z." The conclusion in the original argument isn't ascribing intent to Most Xs.

    1% picked this

  3. Correct

    Studies reveal that people who

    Why this is right

    The evidence in the original argument is comparing two groups, saying something is more prevalent in one than the other. In the original, it's "cars with devices get jacked/robbed more often than those without." In C, it's "regular library users buy more books that people who don't use libraries regularly." The conclusion in the original argument is that one thing does not prevent another: "Antitheft devices don't keep cars from being stolen" In C, it's "using libraries regularly doesn't keep patrons from buying books." The logic in the original argument overlooks a meaningful difference between the two things compared in the evidence: cars with antitheft devices are likely nicer/newer than cars without, and therefore more appealing targets for theives. In C, the author overlooks that people who use libraries regularly are likely bigger readers than those who don't use libraries, making them more likely to both use the library AND buy books. The logic in both arguments also fails to consider that without X that supposedly isn't preventing Y, we'd actually have a lot more Y. Without the devices, even more cars might be stolen. Without the library, even more books might be bought.

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

    73% picked this

  4. Since youngsters who read voraciously

    Bad Conclusion Match

    The evidence in D looks like a good match, but the conclusion in D doesn't assert that one thing doesn't prevent another. It lacks the Anti-Causal flaw and the Sampling flaw we identified in the original. D is more like a Relative/Absolute flaw: just because kids that don't like to read are less likely to have defective vision relative to voratious readers doesn't mean that more than 50% of non-readers have perfect vision.

    18% picked this

  5. Societies that support free public

    Bad Conclusion Match

    The evidence in E looks like a good match, but the conclusion in D doesn't assert that one thing doesn't prevent another. It lacks the Anti-Causal flaw and the Sampling flaw we identified in the original. E is more like a Causal flaw where the author confuses correlation for causation. Just becuse there's a correlation between support for free libraries and free universities doesn't mean that having a free library will cause people to be more supportive of free university.

    4% picked this

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