When new laws imposing strict penalties for misleading corporate

C) Even before the new laws were passed, the information most corporations released was true.

(C) is problematic because we are given in the argument that "amount and accuracy of information disclosed" would increase under new law.
So even if whatever the corps were releasing was true, perhaps they were hiding important information.
For example, if they were telling the truth about their assets but hiding their liabilities, it would still lead to misleading analysis. We now expect to get more and more accurate information so we would expect our analysis to get better.

E) The more pieces of information corporations release, the more difficult it becomes for anyone to organize them in a manageable way.

(E) makes sense because along with the advantage of the new law, it introduces a problem associated with it. That could neutralise the advantage and hence could be responsible for similar number of errors in the analysis as before.
The new law is bringing in advantages as per the argument and there is no debate about that. What we have to show is why our analysis may still be the same, accuracy wise.

The question asks us to find the answer choice that "best" explains the discrepancy in the passage, not the one that perfectly resolves the discrepancy. So we're just looking for the option that provides a better explanation than the other options, even if that answer choice isn't 100% airtight.

(E) tells us that "the more pieces of information corporations release, the more difficult it becomes for anyone to organize them in a manageable way." We know from the passage that the new laws have provided an "increased amount[...] of information."

Putting these two things together, we know that the analysts have a more difficult job managing information under the new law. This new difficulty could, to some extent, counterbalance the helpful things about the new law. So, (E) provides an explanation for the discrepancy in the passage.

Could there be improved models, as you've said? Potentially, but we really don't have any information to support that inference. More to the point, even if there are outlier cases in which (E) isn't a perfect explanation, it still does a better job than any of the other answer choices.

(E) is the correct answer.

I hope that helps!

Though GMATNinja has already explained it brilliantly, I would like add one last point here:

Look at the question stem: Which of the following would, if true, best explain the discrepancy outlined above?

So we need to assume that the data given in the option is true.

E) The more pieces of information corporations release, the more difficult it becomes for anyone to organize them in a manageable way.

The more the information, the more difficult it is to organize in a manageable way. Perhaps which piece will be useful where in the model becomes difficult, perhaps analysts make errors in collating the pieces for the model - we don't know. The point is, it brings in new difficulties and that's what we are told.

Hence, it doesn't matter what our logic tells us from our real world experience, the point is that if it were true that more info is hard to organize properly, then would it explain why accuracy has not improved?

KarishmaB , GMATNinja

Can you please state more statements that if true can help explain this given discrepancy ?

Usually, you can explain a given discrepancy in various ways. That is why pre-thinking is not very useful in such questions.
Here, if we say that the most important pieces of info on which the accuracy of predictions depend are still not available under these laws, then also we can explain the paradox.

Was stuck between A and E.
The error I made- I thought that even when the information and accuracy is increasing, companies might be finding a way out as to what does not construe as 'misleading' and find a way out to only provide the information which does not reflect flaws in their corporate performance. Basically they will find a loophole in the law. I made an additional assumption which is actually a big no-no.
E thus seemed weaker.

Experienced this for the first time, I brought in the biases/ outside information based on my background and observed realities ( I am a chartered accountant thus aware of the possibility of companies wiggling out of the scope of law).

Learnings-
1. DO NOT bring in additional assumptions
2. Beware of your biases in questions you can relate to

Hi Karishma,
option E: can you tell me how we go from "difficult to organize" to "wrong predictions"? This requires an assumption that any data that's difficult to organize leads to less accurate predictions. Why are we assuming that? (From real-life experience, I will say difficult to organize data makes it harder to analyze but doesn't neceesarily lead to inaccurate predictions, esp if the data is of superior quality)

Following this discussion, I believe the real issue is between D and E now. Argument is, if we have to make assumptions to get the question correct, we can do it for either D or E. So why is only E right? I think i can help.
Let us see the assumptions we have to make to get each of these options right:

To make this option right anwer, we have to assume that one of the (or many) other sources must have reduced in their accuracy. And this can explain the descripancy.

To make this option the right option, we have to assume that the increase in difficulty to organize WILL translate into not being able to BETTER organize (Read question again, it says: number of inaccurate analysts' predictions has not in fact decreased (this means, the accuracy either has remained same or has gooten worse).

Now, both seem reasonable. In such a scenario, we have to see which assumption of ours is less biased and hence more likely.

For the assumption in option D, we are assuming that one of the (or many) other sources must have reduced in their accuracy. But is there any support in the options that helps us to go this route? Nope! We just assumed it because we wanted to prove this option correct. One could similarly assume that the accuracy of these sources actually increased and hence claim the option to be incorrect. So, our position here is a bit weak and biased.

Now, for the assumption in option E, do we have any support? A weak support but yes it is there! It says "the more difficult it becomes for anyone to organize them". This essentially says things are becoming more difficult. Therefore, we defientely can not expect something good out of it. At best case, things will remain same, but at worst the accuracy will fall. It is in line with what we expect. So this support gives us a few brownie points here. Hence correct option is E.

Hope it helps.

does a manageable way means = accurate predictions or not? No, So I still think D is the best answer

Remember that on discrepancy questions, we aren't looking for an answer that PROVES the discrepancy MUST exist. We already know that the discrepancy exists, and we're looking for an answer that provides a plausible mechanism for that to happen.

D is of no value, because we already know that there has been a positive change in the amount of information available. Corporations are disclosing more, and so more information is available for analysts to use in making their predictions. The fact that other sources are used doesn't matter. We still want to know why this NEW source of valuable info hasn't improved predictions. Basically, for D to work, we'd need to know that the new info wasn't getting used much or wasn't adding value. Something like this: "Analysts typically do not use information provided by a corporation in making predictions about that corporation's performance."

E, on the other hand, gives us exactly what we need: some NEGATIVE factor that offsets the positive of more info. If the gains in information are offset by a loss in organization, this could be a problem. Does it prove that predictions will not improve? Certainly not. But, since we know that predictions did not improve, is this one possible reason for that failure to improve? Sure.

I have an issue with the explanation. It is stated that the number of inaccurate analysts’ predictions has not in fact decreased.

Now, assume that the overall sample base increases (companies for which the prediction is done), then even if the number of absolute inaccurate predictions stays the same, we can conclude that the accuracy of the analysts has infact increased.

Why cant we look at it from this angle, since its a common GMAT CR question type where they swap percentages with absolutes?

I had marked option B considering this angle

You're right that the overall number of predictions could increase, but we certainly can't assume that this is the case. There is just nothing in the passage that supports such an assumption.

And even if the overall number of predictions DID increase, the information in (B) doesn't explain the discrepancy in the passage. Here's (B):
We just have no idea what this change actually looks like. Perhaps corporations now have to release information in December and June -- how does that impact the number or accuracy of predictions? There is simply no way to know. So, this really doesn't explain why the number of inaccurate predictions has remained constant despite the new laws.

So (B) is out.

As a side note: sometimes you'll notice a really juicy gap in the argument, like you did here. Unfortunately, there's no guarantee that the correct answer choice will address that particular gap at all, so you can't only look for options that tie into that particular thing. (E) gives us an entirely different explanation for the discrepancy, and it is the correct answer.

I hope that helps! ­

­The answer is (E) The more pieces of information corporations release, the more difficult it becomes for anyone to organize them in a manageable way.

- The passage suggests that the new laws increased the amount and accuracy of information disclosed. This implies that before the laws, the information might have been less abundant or less accurate. With more accurate information available, analysts might be expected to make better predictions.

- However, the prediction accuracy hasn't improved. Option (E) suggests a possible reason for this. An overwhelming amount of information, even if accurate, could make it difficult for analysts to effectively analyze and interpret it all. This could lead to inaccurate predictions despite the improved data quality.


Why the other options aren't the best fit:

(A) Ambiguous Definition: While a vague definition could create confusion, it wouldn't necessarily lead to more information or make it harder to analyze (the core issue).

(B) Specific Release Times: This might affect some aspects of analysis, but it doesn't directly address the difficulty of processing a larger volume of data.

(C) Truthful Information Before: This contradicts the passage implying less accurate information before the laws. Even if some past information was true, the increase in overall information could be the problem.

(D) Multiple Information Sources: This is true, but the challenge lies in effectively analyzing the increased amount of corporate data, not the existence of other information sources.­

Hey, I am finding it difficult to choose E over D for two reasons.

I think D is right. If the analysts refer to multiple sources, even if one of the sources becomes more accurate, still the prediction can be inaccurate. Also, they have said "number" of inaccurate predictions, so no reason to check whether the accuracy percentage is increasing or not.

secondly, E says that it becomes more difficult to manageable. You have to make a whole convoluted story to justify why that would mean the analysts would not be able to make accurate predictions

The number of sources doesn't matter because we're talking about an improvement in information compared to the pre-law baseline. Whether the number of sources is 1, 10, or 100, we need to explain why the improvement in information isn't causing a decrease in inaccurate analysts' predictions.

All else equal, if one of the sources becomes better (more info, more accuracy), there's reason to believe that the predictions would only get better, even if only a little, and we need something that would explain why that didn't happen.

In case that's not clear, here's an example: say that before the law there were, on average, 100 inaccurate predictions per year, based on, say, 20 sources. Then the laws get passed and one of those 20 sources gets better, so we expect (or hope) that the number of inaccurate predictions will be lower than the previous average.

But, alas, it's still 100 the year after the new laws are passed. Why didn't the new and better information help? Knowing that there are 20 sources doesn't answer that question -- we already knew that, and we want to know why an improvement in one of the sources didn't improve the prediction stats.

For more on choice (E), check out this post: https://gmatclub.com/forum/when-new-law ... l#p3165898.

For anyone confused with the first statement:

The first statement was absolutely wrong because misleading info is domain of corporates and not analyst. Even if interpretation has been not singular, doesn't mean I should directly term it as misinterpretation in a harmful way. We have an emphatic conclusion that info did become more accurate so this multiple interpretations can hardly be an excuse for analyst's accuracy.

P1: Laws imposing strict penalties for misleading corporate disclosures were passed
P2: It Initiate an era of corporate openness.
P3: the benefit, given the increased amount and accuracy of information disclosed under the new laws, it was assumed that analysts' predictions of corporate performance would become more accurate.
P4: Since the passage of the laws, however, the number of inaccurate analysts' predictions has not in fact decreased.


Which of the following would, if true, best explain the discrepancy outlined above?

(A) The new laws' definition of “misleading information” can be interpreted in more than one way.
(out to scope)

(B) The new laws require corporations in all industries to release information at specific times of the year.
(even if they release info at specific time of year, then also the Accuracy should have improved), Rejected

(C) Even before the new laws were passed, the information most corporations released was true.
but the info has increased, (not able to answer anything), rejected

(D) Analysts base their predictions on information they gather from many sources, not just corporate disclosures.
(suppose out of 10 sources, the one source is the data they get from disclosures, then also it must increase the accuracy, as data increased)

(E) The more pieces of information corporations release, the more difficult it becomes for anyone to organize them in a manageable way.
(yes, its hard to analyzed the more data, so the accuracy due to this remains same, may be accuracy due to previous reason has rectified and errors due to large data comes up)