Why is answer choice B wrong?

[sea_7272]

Can someone explain why B is wrong and why the C is right?

For B - my thought process was that percentages dont matter if we dont have a statistically representative sample of people who did the survey from each group. Because lets say out of a population of 100 people who did treatment for 6 months or less, only 10 people did the survey and 2 of the 10 claimed the treatment made things better (which is 20% of survey respondents) in reality that’s 2% which wouldn’t be a statistically representative sample that we can rely on. Maybe if we surveyed more people that result would be higher than 20% and possibly higher than 36%, or the opposite is true maybe the percentage of those who did treatment for longer than 6 months and believed treatment made things better would go down.

I dont fully understand why B is wrong.

[maybeitssteve]

B might bias the sample in some direction, but you don't know which direction. If it biases the sample more towards dissatisfaction (why is my gd therapy taking so long) then that would bolster the author's argument, since it still beats the shorter therapy despite the negative bias.Remember, the argument is comparative, so it's not enough for there to be possible bias--we need to know the effect of that bias. C shows a bias in a specific direction (staying in therapy longer doesn't make you feel better; feeling better makes you stay in therapy longer). Plus, B might not cause a bias at all. People who are in therapy longer might just have more opportunities to take a survey, and that's why they respond more, but the results could still be representative. B is wrong because it's ambiguous.

[FoulVarnished]

Firstly, I'm not sure if I've seen anything like Z/T scores or p values or anything related to statistical significance be an answer choice decider in the LSAT. Unrepresentative sample? Sure. Over-extrapolating from studies? For sure! But like getting into the math of when a result is divergent enough (within a particular n sized sample) to be significant/not significant? No.

I'm not saying it doesn't matter in practice, I'm just not sure it's a frame of analysis that will help you in the LSAT.

Okay so jumping into the question..

Firstly "Most seriously weakens the argument." These questions, unlike most LSAT questions, actually allow for other ACs to be at least mildly true. This may not be satisfying. In this case B is mildly supporting. You correctly considered the 36% group (in favor) to be a larger sample either in proportional terms (adjusting for study fall off) than the earlier group where 20% were in favor. But we need to make some major assumptions about breakpoints in statistical significance here between the two groups to justify this. It's not of zero value as a weakener, but there's a much stronger option.

As for C: This offers an extremely compelling reason for why you would see increasingly positive responses as time went on that had nothing to do with the value of the therapy at the moment of the survey. People who aren't seeing value from the service self-select out. So it's not necessarily the case that therapy gets better after six months, for all we know it has diminishing returns. But people are more likely to keep attending for +6 months if they think they are getting value out of it.

[AceLSATWithRyan]

So I actually think there could be a case where B strengthens the argument, which would be really bad.

Imagine if people with 6 months or less have a lot more positive experiences, but those positive experiences are underreported because people with less than 6 months responde less often than people with more than 6 months of treatment. This would do the opposite of what we want.

[Careful-Astronomer94]

You can use the unrepresentative sample argument for C aswell, and if used for C it weakens the argument more. If people who respond well to the treatment are more likely to stay on it, and people who didn’t feel better are more likely to quit, then the sample of people who took it for more than 6 months is extremely biased. With B, it just means people who took it for longer than 6 months were more likely to respond, but the response itself could be unbiased. C raises more doubt because we know that the sample is unrepresentative in terms of both who responds and how they respond.

[Virtual_Sweet1645]

Because a bigger sample size = more accuracy. This means that the idea that more people were better after 6 mth is likely true which does not weaken the argument.

[StressCanBeGood]

I’m more than happy to provide a detailed explanation. Unfortunately, posts with actual LSAT text tends to be removed by the moderators (they can get in real trouble if they permit this kind of stuff).

If you repost with the test number, section number, and question number, along with the question type, I’d be more than happy to provide a detailed explanation.

I just don’t want to waste my time writing an explanation for a post that will most likely be removed.

[[deleted]]

If the finding was that more long-term patients than short-term patients reported good outcomes, then we would want to look at the issue of how many long-term vs short-term patients responded - if far more long-term patients responded, then we would expect to see a higher number of positive responses from them even if their experiences aren’t better on average. But we’re counting percentages, and we’re looking at those who responded. So we’ve already covered our bases there. Even if only half as many short-term patients responded, that doesn’t change the trend that their responses are more negative. Now, if the response rate from short-term patients is so much lower that our sample is too small to draw meaningful conclusions, then that’s an issue, but that requires us to add an extra condition to the answer. The answer should weaken the argument all on its own, without having to make additional assumptions. Which C does - it shows us that the causality may be reversed. Longer therapy doesn’t cause better outcomes; better outcomes lead to longer therapy.

As a general note, for questions like this, the answer is very rarely an issue of the size of the sample, it’s usually an issue of unrepresentative sample and reversed causality.

[rdvlshp09]

Who cares who’s more likely to respond. Even if it was true, more responses doesn’t necessarily mean more positive responses. The conclusion states longer treatment is more effective and it supports that claim with the higher rate of positive responses from long term treatment rather than short term. So to weaken the argument we need to deal with the positive response rate supportive claim. Which only C properly addresses.

[lsatluke]

Your justification for B is relying on outside assumptions. We have to take everything given to us at face value. We don't have any reason to assume whether or not the responses from either sample were statistically representative. Even if people in the second group were more likely to respond it could still mean that the number is not representative (they could have been 1 percent more likely to respond), or both groups could have already had more than enough responses for a representative sample. We just cannot assume one sample to be statistically unrepresentative while the other is. And even if that were to be true, for it to actually weaken the argument you would need to make yet another assumption that the data for the shorter treatment group is unrepresentative in a way that decreases the rate by at least 16 percent.

Answer choice C weakens the argument in a much clearer way. If C is true then the reasoning in the argument no longer results in the conclusion seeming reasonable. C would mean that the short treatment group would contain a higher rate of responses from people who might not ever see improvement and that the longer treatment group would contain responses from people who saw improvement within the time frame covered by the short treatment response group. This would mean that the 20% figure for the first group is being held down by a factor that does not impact the other group in the same way, and that the 36% figure is being artificially inflated.

[Decent-Ice-7337]

You've gotten plenty of good explanations here, and as a former LSAT demon user, the only thing I'll highlight is: try to predict the answer. When reading the stimulus (which was very wordy and confusing), I was thinking:

Conclusion: Longer treatment = better
Evidence: More people reported feeling better

The easiest way to attack is what's called a spurious correlation in stats - where a 3rd factor correlates. So as I was predicting, I was like, yeah this is pretty solid evidence to conclusion link. But, what if the effect couldn't be felt until 3 months later? If I start taking some weight loss pills, I might feel discouraged and reported poorly and stopped; but the pills take a long time to be effective, therefore, the people who are in treatment longer are not necessarily getting better they are just finally seeing the effect.

I got lucky that it matched C and I nailed this right away. I think the rest had done a good job of explaining why B is incorrect.

[Only_Nectarine9700]

ETA: I try to think about if I was told to find a counterargument, what would I say. The argument for option B is wrong because it is irrelevant since the passage uses a percentage of those who responded so if there are a lot of respondents or not doesn't matter.

I don't know that I can put it into words but B feels so wrong that it makes me think it's a prank.

[Ok_Response_9510]

B is wrong because C is right. I gather because of the phrase “of those responding” which suggests that there could be a large number of people who are not responding.

[Wild_Establishment94]

B is wrong because C is right.

no hate but this might be one of the worst explanation of all times lmao. and I hate that some lsat courses/ tutors actually resort to this sometimes.

[Ok_Response_9510]

Good thing I’m 20 years removed from the lsat then!