CR-OG - 203 - In Physics journals ..particle accelerators..

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by nonameee » Wed Nov 16, 2011 12:40 pm

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OK. Got it. Thanks a lot again.

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by Thiagaraj » Wed Mar 21, 2012 10:13 am

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Can anyone clarify if A is actually irrelevant or does it strengthen?

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by viviennebeatthegmat » Sun Sep 15, 2013 6:06 am

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I also chose B...
In my opinion, the answer should be the one that most weakens the argument. So in this consequence-only-one-cause type question, the best answer should be the one that provides another cause.

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by Java_85 » Sun Sep 15, 2013 3:55 pm

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IMO also E. others choices are clearly out!

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by Nitin.811g » Fri Sep 20, 2013 10:25 pm

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Definitely E it is.

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by lunarpower » Sat Sep 21, 2013 7:02 am

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Admittedly, there's a problem with the wording of the argument. Specifically, "availability" is unacceptably ambiguous: that word could potentially refer either to the number of PA's available or to the wait time necessary to use one.

The passage clearly uses "availability" to mean the first of these two. (If it meant the second, then the conclusion would be completely unrelated to anything else in the argument.) However, if "availability" is taken to mean both of these things, then a case can be made for choice (B).

Choice (E) is unaffected by this issue and is clearly the correct answer choice, as intended by the author of the problem. But the passage should be rewritten with something more specific in place of "availability".

E.g., if we replace the current conclusion with it is likely that the low number of articles was due to the smaller number of available particle accelerators, then we've got a perfectly good problem whose answer is (E).
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by lunarpower » Sat Sep 21, 2013 7:09 am

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Let's assume that the problematic "availability" thing has been replaced by the words I wrote above.

The speaker wants to establish the reason why fewer PA-related articles were published this year. He/she thinks it's because there were fewer PA's available for experiments.
* If we find evidence for a different explanation, then that weakens the argument.
* If we find evidence AGAINST a different explanation, then that (somewhat) strengthens the argument, because there's one less competing explanation available.
(A) Every article based on experiments with particle accelerators that was submitted for publication last year actually was published.
This gets rid of "Articles were rejected by journals" as a potential explanation, so it helps the argument. Opposite of what we want.
(B) The average time scientists must wait for access to a particle accelerator has declined over the last several years.
This gets rid of "Scientists had to wait longer to conduct their experiments" as a potential explanation, so it helps the argument. Opposite of what we want. (See the post above for the changes necessary to make this choice definitively incorrect.)
(C) The number of physics journals was the same last year as in previous years.
Irrelevant.
If there were fewer journals, this would weaken the argument. If the number remained the same, then irrelevant.
(D) Particle accelerators can be used for more than one group of experiments in any given year.
Irrelevant.
If this is true, then it was also true in previous years. So it doesn't contribute to a comparison.
(E) Recent changes in the editorial policies of several physics journals have decreased the likelihood that articles concerning particle-accelerator research will be accepted for publication.


Winner.
This points to "Articles were rejected by journals", rather than what the speaker thinks, as the real explanation for the decrease.
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by ChrisFic » Tue Nov 12, 2013 7:55 am

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Brent@GMATPrepNow wrote:
onesome wrote: Journalist: In physics journals, the number of articles reporting the results of experiments involving particle accelerators was lower last year than it had been in previous years. Several of the particle accelerators at major research institutions were out of service the year before last for repairs, so it is likely that the low number of articles was due to the decline in availability of particle accelerators.
Which of the following, if true, most seriously undermines the journalist�s argument?
(A) Every article based on experiments with particle accelerators that was submitted for publication last year actually was published.
(B) The average time scientists must wait for access to a particle accelerator has declined over the last several years.
(C) The number of physics journals was the same last year as in previous years.
(D) Particle accelerators can be used for more than one group of experiments in any given year.
(E) Recent changes in the editorial policies of several physics journals have decreased the likelihood that articles concerning particle-accelerator research will be accepted for publication.
The conclusion here is a cause and effect conclusion. That is, the reduced availability of particle accelerators caused the low number of articles.


To weaken an X causes Y argument, we can show that:
- Y causes X
- Z causes Y
- X and Y are coincidental

Answer choice D doesn't accomplish any of the above. It suggests that there shouldn't have been a decline in publications in the first place (since more than 1 experiment can be conducted at an accelerator). I should also add that it if it were the case that each accelerator was already being used at maximum capacity (that is, no more experiments could be conducted at them), then the decreased availability would, indeed, cause a drop in publications. So D does not necessarily hurt the argument.

Answer choice E, however, suggests that something else (i.e., Z causes Y) caused the decline in publications.

Cheers,
Brent
Hey all,

I had trouble with this one as well. In my book (Powerscore) they talk about different ways to attack a causal conclusion:
- Show that while the cause occurs the effect does not
- Show that while the effect occurs the cause did not
- Find an alternate cause for the stated effect
- Show that the state relationship is reversed
- Show that a statistical problem exists with the data used to make the causal statement

The conclusion is essentially: lower number of articles published (effect) because some particle accelerators need to be fixed (cause).

B & D both attack that cause: machines need repair. If the wait to use PAs did not decrease then the decrease in articles is not due to some machines being repaired - hence weakened. If multiple experiments can be conducted on one machine then having less machines should not decrease research. If research has not declined then the less articles published is not due to less working machines - weakened. We only need to weaken it by a slight bit to have a valid answer correct?

I can see why E is correct but B and D also weaken the argument in my opinion. The key word to note here is "Which of the following, if true, most seriously undermines the journalist's argument?"

Which leads me to my question - Which is better to do for a conclusion with a causal statement:
-Show that while the effect occurs the cause does not
OR
-Show that while the cause occurs the effect does not

Obviously it appears like the latter to GMAC but people have pointed out the ambiguity in the term "Recent" with option E. I will admit to some ambiguity in B and D as well.

Bah anyway sorry for the novel and please correct any of my logic or understanding.

Thanks[/b]

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by GMATGuruNY » Tue Nov 12, 2013 9:25 am

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ChrisFic wrote: - Show that, IN ANOTHER CASE, while the effect occurred the cause did not
The phrase in red should be added to the reasoning above.
Generally, a causal argument proceeds as follows:
Premise: A and B are observed together.
Conclusion: A causes B.

One way to weaken the conclusion is to show that -- IN ANOTHER CASE -- B has been observed without A.
To illustrate:
Premise: In a certain study, 1,000 people who ate chocolate every day suffered from depression.
Conclusion: Chocolate causes depression.
Weakener: Last year, a study of 1 gazillion patients who suffered from depression revealed that 99% of these patients had never eaten chocolate.
Since -- in another case -- B (suffering from depression) has been observed without A (eating chocolate), the causal link is weakened.

However, if the premise is that A and B have been observed together, the correct answer choice cannot weaken the conclusion by implying that A did not happen IN THE CASE AT HAND.
A premise is a FACT: it cannot be disputed.
If the argument states as a premise that A happened, the correct answer choice cannot imply that A did NOT happen.

In the CR above, A = a decline in the availability of accelerators.
Answer choice: The average time scientists must wait for access to a particle accelerator has declined over the last several years.
This answer choice seems to suggest that A did not happen: that there has NOT been a decline in the availability of accelerators.
Thus, we should be VERY skeptical of this answer choice.
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by ChrisFic » Thu Nov 14, 2013 4:28 am

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GMATGuruNY wrote:
ChrisFic wrote: - Show that, IN ANOTHER CASE, while the effect occurred the cause did not
The phrase in red should be added to the reasoning above.
Generally, a causal argument proceeds as follows:
Premise: A and B are observed together.
Conclusion: A causes B.

One way to weaken the conclusion is to show that -- IN ANOTHER CASE -- B has been observed without A.
To illustrate:
Premise: In a certain study, 1,000 people who ate chocolate every day suffered from depression.
Conclusion: Chocolate causes depression.
Weakener: Last year, a study of 1 gazillion patients who suffered from depression revealed that 99% of these patients had never eaten chocolate.
Since -- in another case -- B (suffering from depression) has been observed without A (eating chocolate), the causal link is weakened.

However, if the premise is that A and B have been observed together, the correct answer choice cannot weaken the conclusion by implying that A did not happen IN THE CASE AT HAND.
A premise is a FACT: it cannot be disputed.
If the argument states as a premise that A happened, the correct answer choice cannot imply that A did NOT happen.

In the CR above, A = a decline in the availability of accelerators.
Answer choice: The average time scientists must wait for access to a particle accelerator has declined over the last several years.
This answer choice seems to suggest that A did not happen: that there has NOT been a decline in the availability of accelerators.
Thus, we should be VERY skeptical of this answer choice.
I like it! Thank you for pointing that out sir

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by lunarpower » Fri Nov 15, 2013 2:38 am

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ChrisFic wrote:Which leads me to my question - Which is better to do for a conclusion with a causal statement:
-Show that while the effect occurs the cause does not
OR
-Show that while the cause occurs the effect does not
See, this ^^ is the kind of thing that just doesn't make any sense to try to do. It's basically impossible to make rules for this stuff; in fact, CR is on the test because it's basically impossible to make rules for this stuff.
Moreover, there's no reason even to bother trying to generalize, because it's always going to be a million thousand zillion times easier to make the distinctions with normal common sense / real-world thinking.

For instance,
Heavy smoking causes lung cancer.
In this case, the first thing you've listed above is meaningless; e.g., if you show me a bunch of people who have lung cancer from, say, working in a coal mine, that does nothing to weaken the case. On the other hand, the second thing is a thing: if you find me a bunch of heavy smokers who never developed lung cancer, then you've got something there.

The bite of the infected Anopheles mosquito is the vector of malaria.
This time the first thing would be strong counterevidence. If you show me a bunch of malaria patients who have never been bitten by the mosquito, then, so much for that hypothesis. On the other hand, you could have people who've been bitten by the mosquito and gotten lucky (since "is the vector of" doesn't imply that every bite will always transmit malaria).

With normal common sense, these distinctions are very easy to make. If you're going to make "rules", though, you're going to have to keep refining them. (You'd have to notice that lung cancer, in the first example, is something that could perfectly well have more than one cause. In the other example, you'd have to notice "the" vector, implying that there's not supposed to be another vector. And so on.)

In fact, if you study, say, 22 different cause-effect problems, you are very likely to wind up with 22 different "rules". And if you have N different "patterns" for N different problems, then, of course, there actually aren't any patterns at all.

Just think about these things the way you'd think about them in the real world. You can't "game" the CR problems, nor can you get them to fit into neat little patterns. Really, you can't.
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by lunarpower » Fri Nov 15, 2013 2:47 am

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GMATGuruNY wrote:One way to weaken the conclusion is to show that -- IN ANOTHER CASE -- B has been observed without A.
To illustrate:
Premise: In a certain study, 1,000 people who ate chocolate every day suffered from depression.
Conclusion: Chocolate causes depression.
Weakener: Last year, a study of 1 gazillion patients who suffered from depression revealed that 99% of these patients had never eaten chocolate.
Since -- in another case -- B (suffering from depression) has been observed without A (eating chocolate), the causal link is weakened.
Here ^^ is a case in point. By trying to apply "rules", we've arrived at a conclusion that's wrong. In reality, the causal link here is unaffected.
To see why, just replace "depression" with "death", and "eat chocolate" with "jump off a skyscraper".
If I look at the details about a million dead people and 99.99% of them did not jump from skyscrapers, that does nothing to weaken the idea that jumping from a skyscraper will kill you -- it just suggests that most of the dead people died from other causes. The same is true for the "chocolate" example, in which the data are consistent with the idea that 99% of people just get depressed for other reasons.

If the causal hypothesis had been stated the other way around -- Depression causes people to eat chocolate (a much more reasonable hypothesis) -- THEN the given data would call that hypothesis into doubt. Maybe that's what you meant, and you just wrote it backward. But, even if that's what happened, the blame still lies in this whole idea of creating frivolous "rules" for something that's much easier to do with everyday (wo)man-on-the-street type thinking.
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by GMATGuruNY » Fri Nov 15, 2013 4:25 am

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lunarpower wrote:In reality, the causal link here is unaffected.
We're in total agreement that providing examples of the effect without the alleged cause (B without A) does not disprove that A causes B.
Generally, an answer choice that attempts this tactic will be wrong.
But I seem to recall one OA from GMAC that took this tactic.
does nothing to weaken the idea that jumping from a skyscraper will kill you
I don't find this an apt analogy..
Whereas one causal link is speculative (does chocolate cause depression?), the other is not (jumping from a skyscraper almost certainly will kill you -- unless you're very, very lucky).
the blame still lies in this whole idea of creating frivolous "rules" for something that's much easier to do with everyday (wo)man-on-the-street type thinking.
Here, we diverge.
What's easy for some test-takers is not so easy for others.
GMAT CRs and OAs do exhibit discernible patterns.
I've seen many students raise their level of accuracy -- considerably -- by learning to recognize these patterns.
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by David@VeritasPrep » Fri Nov 15, 2013 7:36 am

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I agree with Ron and with Mitch and I actually think they agree with each other as I will explain.

First let me reiterate that the Powerscore book is an LSAT book with the word GMAT added to the title.. Take this quote as a Prime example:
I had trouble with this one as well. In my book (Powerscore) they talk about different ways to attack a causal conclusion:
- Show that while the cause occurs the effect does not
- Show that while the effect occurs the cause did not
- Find an alternate cause for the stated effect
- Show that the state relationship is reversed
- Show that a statistical problem exists with the data used to make the causal statement
Are you kidding me? This is straight from an LSAT course where formal logic is used and Critical Reasoning (called logical reasoning on the LSAT) is 50% of the ENTIRE score. In the LSAT course that I teach we spend around 40 hours on logical reasoning! That is longer than an entire GMAT course.

This whole idea of making a rule for every tiny thing drives me crazy. I just had a discussion with a student on the data sufficiency discussion board who simply would not accept a simple mathematical truth about absolute value because it did not fit the two special rules that he had found! Why are you trying to memorize special rules for this one very specific thing anyway? Just test the numbers if you need to.

I do not know why people want to make things more complicated!

I tell people in my courses that if they want to score higher on the verbal section than they need to make things simpler and not more complicated.

This is where I agree with what Ron is saying. Success in critical reasoning is not about memorizing rules, but about understanding arguments.

What I teach on critical reasoning is focus. Different types of critical reasoning questions require a different focus. This is where I agree with Mitch that "I've seen many students raise their level of accuracy by learning to recognize these patterns." The way that I think about this is that critical reasoning should be a natural skill, but it often is not.

So here is where I think that Ron and Mitch agree. Most students need some help to develop their reasoning skills. Yet the development should be one of focusing on the correct portions of the argument so that critical reasoning does become natural. Those who score well on critical reasoning generally have a "feel" for the arguments rather than relying on rules. But it is possible to help them develop that feel. And as instructors we can and should do so.

Of course that is just my take on things!
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by lunarpower » Fri Nov 15, 2013 8:19 am

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GMATGuruNY wrote:
lunarpower wrote:In reality, the causal link here is unaffected.
We're in total agreement that providing examples of the effect without the alleged cause (B without A) does not disprove that A causes B.
Well, agreement some of the time. Which, I guess, isn't really agreement. (:

My point above was, essentially, "Sometimes that will disprove cause/effect. Sometimes it won't." So I tried to make up one example of each. If someone tried to memorize "xxxx does not disprove that a causes b", then that would work fine on the skyscraper example, but the anopheles mosquito example would become impervious to that person's understanding.
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