UVA $$ V. Penn $ Forum

[suralin]

If someone is trying to show that one school has an advantage over another in a specific market, the data I've given should substantially bolster that argument.

It really doesn't. It shows what people do, not what they have the option of doing. There's a gulf between the two things.

I don't think there's a "gulf" between the two things - they're very much interrelated. A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more. (I asked the question to a few partners - NU alums - whether they gave a little edge to the NU students they saw at callbacks, and nearly all of them said yes.) Also, I think that a firm that continues to see a greater number of Penn students in its office would likely heighten its Penn-related recruiting efforts.

Pretty sure you're moving the goalposts now. You asserted that your data substantially bolstered your claim, but now you're relying on anecdotal evidence and intuition?

[igo2northwestern]

Imagine you were trying to write a conclusion for a statistics paper; would your data really support your conclusion?

Whether my data substantially bolsters the claim that one school has an advantage over another in a specific market? If I were to write a stats paper (on correlation), yes.

I don't think there's a "gulf" between the two things - they're very much interrelated. A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more. (I asked the question to a few partners - NU alums - whether they gave a little edge to the NU students they saw at callbacks, and nearly all of them said yes.) Also, I think that a firm that continues to see a greater number of Penn students in its office would likely heighten its Penn-related recruiting efforts.

Pretty sure you're moving the goalposts now. You asserted that your data substantially bolstered your claim, but now you're relying on anecdotal evidence and intuition?

Pretty sure I made two consistent points. I don't understand why it's difficult to see that anecdotal evidence and data can support the same claim. Isn't that how people, you know, make arguments?

[FlightoftheEarls]

A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more.

Assuming this is the case, how does this change the fact that the schools have nearly identical average offer GPAs after accounting for median differences? Still assuming your claim is true but going even further, what would it suggest to you about a how a firm would treat Penn students were it not for those partners? Do you still find this to be a convincing argument?

Also, I think that a firm that continues to see a greater number of Penn students in its office would likely heighten its Penn-related recruiting efforts.

I can't imagine a firm where this is the case. I actually suspect this only happens when a firm suddenly notices a drop off in its recruiting efforts at a particular school where it regularly recruits.

[suralin]

Imagine you were trying to write a conclusion for a statistics paper; would your data really support your conclusion?

Whether my data substantially bolsters the claim that one school has an advantage over another in a specific market? If I were to write a stats paper (on correlation), yes.

I don't think there's a "gulf" between the two things - they're very much interrelated. A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more. (I asked the question to a few partners - NU alums - whether they gave a little edge to the NU students they saw at callbacks, and nearly all of them said yes.) Also, I think that a firm that continues to see a greater number of Penn students in its office would likely heighten its Penn-related recruiting efforts.

Pretty sure you're moving the goalposts now. You asserted that your data substantially bolstered your claim, but now you're relying on anecdotal evidence and intuition?

Pretty sure I made two consistent points. I don't understand why it's difficult to see that anecdotal evidence and data can support the same claim. Isn't that how people, you know, make arguments?

Re: the parenthetical, that's my point? How exactly does your data, which merely shows a correlation, demonstrate what you call a real advantage?

Re: your two consistent points, I'm pointing out that first you relied on data, and then when challenged, you backed off and depended on intuition and a story.

[igo2northwestern]

A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more.

Assuming this is the case, how does this change the fact that the schools have nearly identical average offer GPAs after accounting for median differences? Still assuming your claim is true but going even further, what would it suggest to you about a how a firm would treat Penn students were it not for those partners? Do you still find this to be a convincing argument?

I don't think this is an established fact. In fact, based on the link you provided earlier, it's very much a conjecture.

Also, I think that a firm that continues to see a greater number of Penn students in its office would likely heighten its Penn-related recruiting efforts.

I can't imagine a firm where this is the case. I actually suspect this only happens when a firm suddenly notices a drop off in its recruiting efforts at a particular school where it regularly recruits.[/quote]
That doesn't make a lot of sense to me... but we can agree to disagree. I should clarify, I meant "a firm that continues to see a greater # of Penn students in its office would likely have greater Penn-related recruiting efforts (adjusting for class size)".

[igo2northwestern]

Re: the parenthetical, that's my point? How exactly does your data, which merely shows a correlation, demonstrate what you call a real advantage?

Re: your two consistent points, I'm pointing out that first you relied on data, and then when challenged, you backed off and depended on intuition and a story.

* I think you're contorting what I said... I thought we had it clear what my conclusion was. My conclusion was that the "data substantially bolsters the conclusion that one school has an advantage over another in a specific market." "Substantially bolsters" =/= "demonstrates". I never said that a conclusion about Penn's advantage can be exclusively drawn from my data.

* The above statement probably clarifies things, but I should add that the conversation was not the dramatic picture you're painting.

[suralin]

Re: the parenthetical, that's my point? How exactly does your data, which merely shows a correlation, demonstrate what you call a real advantage?

Re: your two consistent points, I'm pointing out that first you relied on data, and then when challenged, you backed off and depended on intuition and a story.

* I think you're contorting what I said... I thought we had it clear what my conclusion was. My conclusion was that the "data substantially bolsters the conclusion that one school has an advantage over another in a specific market." "Substantially bolsters" =/= "demonstrates". I never said that a conclusion about Penn's advantage can be exclusively drawn from my data.

* The above statement probably clarifies things, but I should add that the conversation was not the dramatic picture you're painting.

Okay, that makes more sense. I still disagree that your data, in fact, bolsters the conclusion that one school has an advantage: showing correlation does not do more to support a claim (it's not as if a correlation either demonstrates or bolsters a claim; it can be the case that a correlation does nothing) particularly if there are valid concerns raised about self-selection, ability to do vs. doing per se, etc.

In short, you're saying that the data you've provided plus your anecdotal evidence/intuition makes the case that one school has an advantage over another, whereas I disagree both that the data shows a causal link and that your anecdotal evidence/intuition provides more support.

[igo2northwestern]

Okay, that makes more sense. I still disagree that your data, in fact, bolsters the conclusion that one school has an advantage: showing correlation does not do more to support a claim (it's not as if a correlation either demonstrates or bolsters a claim; it can be the case that a correlation does nothing) particularly if there are valid concerns raised about self-selection, ability to do vs. doing per se, etc.

In short, you're saying that the data you've provided plus your anecdotal evidence/intuition makes the case that one school has an advantage over another, whereas I disagree both that the data shows a causal link (we agree I never said this..) and that your anecdotal evidence/intuition provides more support.

Through all this, don't you think it's a bit frustrating that you position yourself in an adversarial manner to argue against statements I've never made? Frankly, I don't really care so much what sorts of reservations you have on the utility of correlation analyses. I don't need a stats education - I raised the point concerning correlation entirely because you (kinda condescendingly) asked me to "imagine myself writing a stats paper".

And now that you've muddled over the fact that you misunderstood what my conclusion was in the first place, you disagree with me once more about a conversation that I had with another person... without substantiation.

[suralin]

Okay, that makes more sense. I still disagree that your data, in fact, bolsters the conclusion that one school has an advantage: showing correlation does not do more to support a claim (it's not as if a correlation either demonstrates or bolsters a claim; it can be the case that a correlation does nothing) particularly if there are valid concerns raised about self-selection, ability to do vs. doing per se, etc.

In short, you're saying that the data you've provided plus your anecdotal evidence/intuition makes the case that one school has an advantage over another, whereas I disagree both that the data shows a causal link (we agree I never said this..) and that your anecdotal evidence/intuition provides more support.

Through all this, don't you think it's a bit frustrating that you position yourself in an adversarial manner to argue against statements I've never made? Frankly, I don't really care so much what sorts of reservations you have on the utility of correlation analyses. I don't need a stats education - I raised the point concerning correlation entirely because you (kinda condescendingly) asked me to "imagine myself writing a stats paper".

And now that you've muddled over the fact that you misunderstood what my conclusion was in the first place, you disagree with me once more about a conversation that I had with another person... without substantiation.

I'm sorry, but I truly don't see how I've been anything less than charitable. If you agree with me, then how does your conclusion follow? If you agree that your data just shows a correlation, then how does that support what you're saying? (Because you don't think there's a causal link, right?) That's all I'm asking.

ETA: Either your data shows a causal link and thereby supports your argument (going to that school causes one to have an advantage over another school) or it shows correlation and doesn't thereby support your argument. If we agree--like you just said--that it (just) shows correlation, I don't see what's left to quibble over.

[FlightoftheEarls]

A firm that has a large Penn footprint I would assume pushes for Penn candidates a bit more.

Assuming this is the case, how does this change the fact that the schools have nearly identical average offer GPAs after accounting for median differences? Still assuming your claim is true but going even further, what would it suggest to you about a how a firm would treat Penn students were it not for those partners? Do you still find this to be a convincing argument?

I don't think this is an established fact. In fact, based on the link you provided earlier, it's very much a conjecture.

Which part of looking at the actual offer data provided by each school's OCS and determining where that average GPA lands within each school's class do you object to? I admittedly have not seen the Penn data for every firm, but so far each has pointed towards very similar treatment of the schools. IAFG has apparently also seen average offer data for these schools and reached the same conclusion. By comparison, you're looking at data that's completely removes the possibility anybody might want an outcome other than NLJ250 (including even a clerkship, if you're relying on your quakeroats-esque firm bio count) and suggesting this as a better basis for comparing how firms treat each school than the actual information about how deep in each school's class a firm will typically gives its offers.

Could you perhaps explain a bit more why you think this is a better approach?

[Ti Malice]

Okay, that makes more sense. I still disagree that your data, in fact, bolsters the conclusion that one school has an advantage: showing correlation does not do more to support a claim (it's not as if a correlation either demonstrates or bolsters a claim; it can be the case that a correlation does nothing) particularly if there are valid concerns raised about self-selection, ability to do vs. doing per se, etc.

In short, you're saying that the data you've provided plus your anecdotal evidence/intuition makes the case that one school has an advantage over another, whereas I disagree both that the data shows a causal link (we agree I never said this..) and that your anecdotal evidence/intuition provides more support.

Through all this, don't you think it's a bit frustrating that you position yourself in an adversarial manner to argue against statements I've never made? Frankly, I don't really care so much what sorts of reservations you have on the utility of correlation analyses. I don't need a stats education - I raised the point concerning correlation entirely because you (kinda condescendingly) asked me to "imagine myself writing a stats paper".

And now that you've muddled over the fact that you misunderstood what my conclusion was in the first place, you disagree with me once more about a conversation that I had with another person... without substantiation.

I'm sorry, but I truly don't see how I've been anything less than charitable. If you agree with me, then how does your conclusion follow? If you agree that your data just shows a correlation, then how does that support what you're saying? (Because you don't think there's a causal link, right?) That's all I'm asking.

ETA: Either your data shows a causal link and thereby supports your argument (going to that school causes one to have an advantage over another school) or it shows correlation and doesn't thereby support your argument. If we agree--like you just said--that it (just) shows correlation, I don't see what's left to quibble over.

This post really should be the end of this discussion.

[igo2northwestern]

I'm sorry, but I truly don't see how I've been anything less than charitable. If you agree with me, then how does your conclusion follow? If you agree that your data just shows a correlation, then how does that support what you're saying? (Because you don't think there's a causal link, right?) That's all I'm asking.

ETA: Either your data shows a causal link and thereby supports your argument (going to that school causes one to have an advantage over another school) (this is the xth time I've made the point that this was not my argument - see above) or it shows correlation and doesn't thereby support your argument. If we agree--like you just said--that it (just) shows correlation, I don't see what's left to quibble over.

I don't think you understand the difference between causation and correlation. I also think you consistently confuse the difference between a statement that provides support and a statement that makes a conclusion. A correlation can most certainly support a claim that going to a school causes one to have an advantage over another -- an argument that another poster on this thread made. You don't need to demonstrate a direct, causal link to bolster the argument that going to one school brings an employment advantage.

Sure, the data that I provided "just" shows correlation. But you seem to think that all correlations should be discredited; this ignores the potential for it to be a statistically significant one. Now, I did not make the claim that it is a statistically significant one. If you read back, I did not make the claim that the data "demonstrates" a causal connection either.

But does it bolster another poster's claim? Certainly.

Which part of looking at the actual offer data provided by each school's OCS and determining where that average GPA lands within each school's class do you object to? I admittedly have not seen the Penn data for every firm, but so far each has pointed towards very similar treatment of the schools. IAFG has apparently also seen average offer data for these schools and reached the same conclusion. By comparison, you're looking at data that's completely removes the possibility anybody might want an outcome other than NLJ250 (including even a clerkship, if you're relying on your quakeroats-esque firm bio count) and suggesting this as a better basis for comparing how firms treat each school than the actual information about how deep in each school's class a firm will typically gives its offers.

Could you perhaps explain a bit more why you think this is a better approach?

I do think that the approach of determining specific cut-off %s is better. From what I've read in the thread you cited though, there is a sufficient amount of "probably"s, "likely"s, and "somewhere in the range of"s that would make your claim less bulletproof than you make it to be right now. If you have offer data that (nearly) every student in both Penn and UVa has accurately provided, in recent years, and if you have confirming data on the GPAs that correspond to students' ranks, then yeah I think we can definitively tell whether a school has firm placement advantage in a specific market.

At least at my school, the stats are less solid -- in the most recent year, the data is based on 30% of students' self-reporting. Further, our GPA stats are a black box -- I know that our median is "roughly" a B+, and I don't know whether a 3.7 is top 10% or top 20%. Maybe I'm wrong about the ones you have collected? If so, then of course I think your method concerning employment stats is the single one we should use when comparing the two schools' firm prospects in a specific region. If not, then we'll sit back in the gray room, in which we conjecture and may make claims like... doesn't a biocount with higher Penn representation support the claim that Penn has an advantage in NY?

[suralin]

I'm sorry, but I truly don't see how I've been anything less than charitable. If you agree with me, then how does your conclusion follow? If you agree that your data just shows a correlation, then how does that support what you're saying? (Because you don't think there's a causal link, right?) That's all I'm asking.

ETA: Either your data shows a causal link and thereby supports your argument (going to that school causes one to have an advantage over another school) (this is the xth time I've made the point that this was not my argument - see above) or it shows correlation and doesn't thereby support your argument. If we agree--like you just said--that it (just) shows correlation, I don't see what's left to quibble over.

I don't think you understand the difference between causation and correlation. I also think you consistently confuse the difference between a statement that provides support and a statement that makes a conclusion. A correlation can most certainly support a claim that going to a school causes one to have an advantage over another -- an argument that another poster on this thread made. You don't need to demonstrate a direct, causal link to bolster the argument that going to one school brings an employment advantage.

Sure, the data that I provided "just" shows correlation. But you seem to think that all correlations should be discredited; this ignores the potential for it to be a statistically significant one. Now, I did not make the claim that it is a statistically significant one. If you read back, I did not make the claim that the data "demonstrates" a causal connection either.

But does it bolster another poster's claim? Certainly.

I don't really think you're justified in claiming I don't understand the difference between causation and correlation, but if you want to say that, sure.

If your argument is not that the data you provided bolsters the claim that x student going to Penn has an advantage over x student going to UVA in the NY market ceteris paribus, then what is your argument?

Okay, the bolded is the root of our disagreement then. I clearly said previously that not only does a correlation not provide support (at least in favor of a causal link, of course it provides support for a correlation but that's not the claim made), it can in fact do nothing at all, particularly when countervailing variables are present--e.g., self-selection bias, distinction between what people do and what they have the ability to do.

Also, of course you don't need to demonstrate a causal link to bolster a causal argument (in your words), but you do need sufficiently modeled data even merely for bolstering--your argument turns on whether the data is sufficient for support and I'm saying straightforwardly that it's clearly not.

That is, I'm disputing that the data bolsters the claim that x student going to Penn has an advantage over x student going to UVA, and my disagreement goes to the fact that it takes a certain kind of data (see, of course, the counterfactual models found in Pearl's work) to bolster the kind of claim being presented: the data presented is not the right sort.

Do you not see that countervailing variables can completely remove any bolstering effect of data, especially the weak sort of data shown? Or that data showing a correlation does not have to either demonstrate or bolster/support, it can just do nothing at all for a claim?

[TrialLawyer16]

Okay, that makes more sense. I still disagree that your data, in fact, bolsters the conclusion that one school has an advantage: showing correlation does not do more to support a claim (it's not as if a correlation either demonstrates or bolsters a claim; it can be the case that a correlation does nothing) particularly if there are valid concerns raised about self-selection, ability to do vs. doing per se, etc.

In short, you're saying that the data you've provided plus your anecdotal evidence/intuition makes the case that one school has an advantage over another, whereas I disagree both that the data shows a causal link (we agree I never said this..) and that your anecdotal evidence/intuition provides more support.

Through all this, don't you think it's a bit frustrating that you position yourself in an adversarial manner to argue against statements I've never made? Frankly, I don't really care so much what sorts of reservations you have on the utility of correlation analyses. I don't need a stats education - I raised the point concerning correlation entirely because you (kinda condescendingly) asked me to "imagine myself writing a stats paper".

And now that you've muddled over the fact that you misunderstood what my conclusion was in the first place, you disagree with me once more about a conversation that I had with another person... without substantiation.

I'm sorry, but I truly don't see how I've been anything less than charitable. If you agree with me, then how does your conclusion follow? If you agree that your data just shows a correlation, then how does that support what you're saying? (Because you don't think there's a causal link, right?) That's all I'm asking.

ETA: Either your data shows a causal link and thereby supports your argument (going to that school causes one to have an advantage over another school) or it shows correlation and doesn't thereby support your argument. If we agree--like you just said--that it (just) shows correlation, I don't see what's left to quibble over.

This post really should be the end of this discussion.

+1. He was owned pretty handily in that last paragraph.

[igo2northwestern]

I don't really think you're justified in claiming I don't understand the difference between causation and correlation, but if you want to say that, sure.

If your argument is not that the data you provided bolsters the claim that x student going to Penn has an advantage over x student going to UVA in the NY market ceteris paribus, then what is your argument?

Okay, the bolded is the root of our disagreement then. I clearly said previously that not only does a correlation not provide support (at least in favor of a causal link, of course it provides support for a correlation but that's not the claim made), it can in fact do nothing at all, particularly when countervailing variables are present--e.g., self-selection bias, distinction between what people do and what they have the ability to do.

Also, of course you don't need to demonstrate a causal link to bolster a causal argument (in your words), but you do need sufficiently modeled data even merely for bolstering--your argument turns on whether the data is sufficient for support and I'm saying straightforwardly that it's clearly not.

That is, I'm disputing that the data bolsters the claim that x student going to Penn has an advantage over x student going to UVA, and my disagreement goes to the fact that it takes a certain kind of data (see, of course, the counterfactual models found in Pearl's work) to bolster the kind of claim being presented: the data presented is not the right sort.

Do you not see that countervailing variables can completely remove any bolstering effect of data, especially the weak sort of data shown? Or that data showing a correlation does not have to either demonstrate or bolster/support, it can just do nothing at all for a claim?

Oh I see where our point of disagreement is, and I think it's a semantic one. My argument is that the data I provided supports the claim that x student going to Penn has an advantage over x student going to UVA in the NY market, nocte te tangis. My argument was not, at the time, that x student going to Penn has an advantage over x student going to UVA in the NY market.

That aside, we also have a disagreement on whether it is necessary to test the correlation between employment outcomes and school choice in order to support the above claim. It seems, to you, that I need to construct an empirical model and demonstrate the statistical significance of Penn's presence at NY in order to show Penn Law's advantage there. But even then, I'd probably receive a strew of other criticisms -- my choice of model was unsuitable, it did not account for xyz variables, the amount by which one variable mitigates another was unfairly assumed, the matter at hand cannot be tested, etc. See, it's pretty easy to criticize data. Any bystander can look at a set of numbers and say that it paints an incomplete picture; in fact that's why correlation studies are contested by... wait for it... other correlation studies. Your insight applies to almost everything, because a small, unnoticed change to something could turn everything on its head.

So why don't you conduct your Pearl analysis over the last few years to infer the grade cut-offs at NY firms? Oh wait. You can't. Because you don't actually have information on school-specific OCI performance. I don't think it's available even to students. Am I wrong? If this is correct, would the conclusion then be that we cannot statistically test the relative strength of two schools? Maybe we can't for lack of reporting, and I think this what you're trying to say. You're telling me that the famous self-selection defense and the students' decisions themselves are responsible for an inflated Penn NY presence.

Well, I haven't made the argument yet, but I'll make it now: if you are a student looking to practice at a top law firm in New York, all else equal, go to the school that has a greater proportion of alumni. The data supports this simple logic, even if I haven't "proven" a statistically significant correlation.

[suralin]

I don't really think you're justified in claiming I don't understand the difference between causation and correlation, but if you want to say that, sure.

If your argument is not that the data you provided bolsters the claim that x student going to Penn has an advantage over x student going to UVA in the NY market ceteris paribus, then what is your argument?

Okay, the bolded is the root of our disagreement then. I clearly said previously that not only does a correlation not provide support (at least in favor of a causal link, of course it provides support for a correlation but that's not the claim made), it can in fact do nothing at all, particularly when countervailing variables are present--e.g., self-selection bias, distinction between what people do and what they have the ability to do.

Also, of course you don't need to demonstrate a causal link to bolster a causal argument (in your words), but you do need sufficiently modeled data even merely for bolstering--your argument turns on whether the data is sufficient for support and I'm saying straightforwardly that it's clearly not.

That is, I'm disputing that the data bolsters the claim that x student going to Penn has an advantage over x student going to UVA, and my disagreement goes to the fact that it takes a certain kind of data (see, of course, the counterfactual models found in Pearl's work) to bolster the kind of claim being presented: the data presented is not the right sort.

Do you not see that countervailing variables can completely remove any bolstering effect of data, especially the weak sort of data shown? Or that data showing a correlation does not have to either demonstrate or bolster/support, it can just do nothing at all for a claim?

Oh I see where our point of disagreement is, and I think it's a semantic one. My argument is that the data I provided supports the claim that x student going to Penn has an advantage over x student going to UVA in the NY market, nocte te tangis. My argument was not, at the time, that x student going to Penn has an advantage over x student going to UVA in the NY market.

That aside, we also have a disagreement on whether it is necessary to test the correlation between employment outcomes and school choice in order to support the above claim. It seems, to you, that I need to construct an empirical model and demonstrate the statistical significance of Penn's presence at NY in order to show Penn Law's advantage there. But even then, I'd probably receive a strew of other criticisms -- my choice of model was unsuitable, it did not account for xyz variables, the amount by which one variable mitigates another was unfairly assumed, the matter at hand cannot be tested, etc. See, it's pretty easy to criticize data. Any bystander can look at a set of numbers and say that it paints an incomplete picture; in fact that's why correlation studies are contested by... wait for it... other correlation studies. Your insight applies to almost everything, because a small, unnoticed change to something could turn everything on its head.

So why don't you conduct your Pearl analysis over the last few years to infer the grade cut-offs at NY firms? Oh wait. You can't. Because you don't actually have information on school-specific OCI performance. I don't think it's available even to students. Am I wrong? If this is correct, would the conclusion then be that we cannot statistically test the relative strength of two schools? Maybe we can't for lack of reporting, and I think this what you're trying to say. You're telling me that the famous self-selection defense and the students' decisions themselves are responsible for an inflated Penn NY presence.

Well, I haven't made the argument yet, but I'll make it now: if you are a student looking to practice at a top law firm in New York, all else equal, go to the school that has a greater proportion of alumni. The data supports this simple logic, even if I haven't "proven" a statistically significant correlation.

LOL nocte te tangis? Mature. I don't understand why you're so worked up about this. Do you go to Penn by chance?

It seems you think that I'm motivated in my reasoning or that I'm engaging in confirmation bias, but I have no dog in the fight: I attend neither Penn nor UVA. I don't really care about changing your mind--apparently it's already made up--but I do care about others reading this and drawing unwarranted conclusions from the data you presented.

Also, this whole time you were trying to pretend the bolded wasn't implicitly your claim. LOL. You can make arguments like that all you want, just don't get so upset when people point out that the argument doesn't hold water. Also, "statistically significant" doesn't mean what you think it means, and neither does "Pearl analysis."

[Cobretti]

NLJ may be a good way to determine placement, but it is a pretty terrible way to determine placement ability. The only thing that matters is how deep into a law school class a firm will go, and none of that data for Penn suggests that it has any distinct advantage over MVPDN.

Here's a thread that lays out I'm talking about: http://top-law-schools.com/forums/viewt ... 8&start=25

Here's some better data

Vault V5:
Wachtell | UVa: 2 attnys, Penn: 18 attnys
Cravath | UVa: 8, Penn: 25
Sullivan | UVa: 31, Penn: 42
Skadden | UVa: 44, Penn: 53
Davis Polk | UVa: 26, Penn: 27
V5 Total | UVa: 111, Penn: 165
V5 Per Capita| UVa: 0.31, Penn: 0.68

Non-NY Based Elite:
Kirkland (Chi) | UVa: 39, Penn: 30
Latham (NY/LA) | UVa: 72, Penn: 44
Covington (DC) | UVa: 35, Penn: 23
Gibson (LA) | UVa: 34, Penn: 38
Sidley (Chi) | UVa: 48, Penn: 32
Williams & Connoly (DC) | UVa: 30; Penn: 16
Quinn (LA) | UVa: 15, Penn: 9
MoFo (SF) | UVa: 22, Penn: 25
Ropes & Gray (Boston) | UVa: 24, Penn: 28
Wilmerhale (DC) | UVa: 31, Penn: 28
Keker (SF) | UVa: 1, Penn: 1
Irell (LA) | UVa: 1, Penn: 5
"Non-NY" Total | UVa: 352, Penn: 279
"Non-NY" Per Capita | UVa: 0.99, Penn: 1.15

Penn class size: 243
UVa class size: 357

Unfortunately this ignores the very point I'm making by showing raw numbers from firm bios in place of NLJ percentages. It does nothing to explain placement ability any more than NLJ percentages does and is actually subject to even more variables than the NLJ hiring data.

I've compared notes on CB data with people at Mich, Penn, and Cornell and my impression was they're all about the same, despite having widely different placement stats. The reason it's not already compiled on TLS, I assume, is because schools tell us to keep that data to ourselves. Every T14 2L and 3L should have access to that information for their own school though.

Edit: also, I object to V20 NYC being our benchmark for "prestige." I would assume lots of GULC/UVA students would rather work for a lower V100 DC firm than an NYC V10.

This. It's a little frustrating not being able to share this data on TLS, but I (and quite possibly many others) don't want to publicly distribute this information only to be subject to the fallout that may or may not come with that. I'll admit (this is embarrassing) that the competitive side of me has begun drafting posts in several threads breaking down just how similar Michigan and Penn are based on the average offer GPAs I've seen, but I've had to resist the urge to post this information because it's just not worth proving a point on TLS. If you can get your hands on this data from a friend at another school, I think you'll be quite surprised by (1) how similar the average GPAs are at most firms after accounting for different school medians and (2) how mediocre of a metric the NLJ data is for any single student targeting NYC biglaw.

60k is a ton of money. I know it doesn't seem like it to those of you who are deciding on school, but I beg you to understand that it really is.

This may end up being the best post in this entire thread. I've been on TLS since I began my law school application process, and I started paying my loans in November of this year. As someone who has spanned the full TLS "lifecycle", I can vouch that what once almost seemed like monopoly money when deciding between schools is now incredibly real.

Thanks man, this is great advice. Knowing what you know now, would you say 60k at NU would be better than sticket at UPenn? Are the CB numbers even that similar from 7 to 12?

[igo2northwestern]

LOL nocte te tangis? Mature. I don't understand why you're so worked up about this. Do you go to Penn by chance?

It seems you think that I'm motivated in my reasoning or that I'm engaging in confirmation bias, but I have no dog in the fight: I attend neither Penn nor UVA. I don't really care about changing your mind--apparently it's already made up--but I do care about others reading this and drawing unwarranted conclusions from the data you presented.

Also, this whole time you were trying to pretend the bolded wasn't implicitly your claim. LOL. You can make arguments like that all you want, just don't get so upset when people point out that the argument doesn't hold water. Also, "statistically significant" doesn't mean what you think it means, and neither does "Pearl analysis."

I'm not worked up, my mature friend. If I were worked up, I wouldn't have written that; I would have instead pervaded my arguments with "LOL". I was amused that you cited Latin in your response. Similarly, that's why I wrote "Pearl analysis". Again, it's subtle (maybe too subtle) mockery of the fact that you cited him in the first place. And that's fine if you don't think I understand what statistically significant means.

Oh the bolded was implicitly my claim -- good job -- but never did I make a claim on data alone (and actually, I didn't make that claim until much, much later..); if you had read carefully, you'd have seen that it wasn't my point.

[suralin]

LOL nocte te tangis? Mature. I don't understand why you're so worked up about this. Do you go to Penn by chance?

It seems you think that I'm motivated in my reasoning or that I'm engaging in confirmation bias, but I have no dog in the fight: I attend neither Penn nor UVA. I don't really care about changing your mind--apparently it's already made up--but I do care about others reading this and drawing unwarranted conclusions from the data you presented.

Also, this whole time you were trying to pretend the bolded wasn't implicitly your claim. LOL. You can make arguments like that all you want, just don't get so upset when people point out that the argument doesn't hold water. Also, "statistically significant" doesn't mean what you think it means, and neither does "Pearl analysis."

I'm not worked up, my mature friend. If I were worked up, I wouldn't have written that; I would have instead pervaded my arguments with "LOL". I was amused that you cited Latin in your response. Similarly, that's why I wrote "Pearl analysis". Again, it's subtle (maybe too subtle) mockery of the fact that you cited him in the first place. And that's fine if you don't think I understand what statistically significant means.

Oh the bolded was implicitly my claim -- good job -- but never did I make a claim on data alone (and actually, I didn't make that claim until much, much later..); if you had read carefully, you'd have seen that it wasn't my point.

I said ceteris paribus because I was trying to be precise and not strawman your argument. In the same way, I mentioned Pearl's work because I was trying to point to examples of ways that data can be modeled or intervened with to, in your words, bolster a causal claim. Why would you mock that? Would you rather have me make arguments without examples or references, or without being precise?

I was saying "LOL" because it seemed that you were deliberately being as uncharitable and logically rude as possible in responding to me, which was frustrating because I truly wanted to see your point--which, by the way, you never actually explicitly laid out.

Also, your use of statistically significant is completely irrelevant, which again seemed like you were just trying to "win" an argument without even reading my points (ironic by the way). Data can be statistically significant in showing a pattern or correlation, yet not support a claim; that doesn't seem controversial or non-obvious at all.

No hard feelings. The discussion was good in clarifying my own thoughts.

[bigstin]

GPA cutoff is important, but it'd be more useful if we knew the number of offers a firm gave as well. Firm X may have a gpa cutoff of top 1/3 at both Penn and UVA but may give offers to only 5 students above the cutoff at each school. By virtue of being a smaller school, a student at Penn would have a better chance of getting an offer than one at UVA if the actual number of offers given above the GPA cutoff are the same. It really seems like there are a lot of factors to take into account. Purely looking at NLJ numbers or at GPA cutoffs will probably not give you the full story.

[HeavenWood]

GPA cutoff is important, but it'd be more useful if we knew the number of offers a firm gave as well. Firm X may have a gpa cutoff of top 1/3 at both Penn and UVA but may give offers to only 5 students above the cutoff at each school. By virtue of being a smaller school, a student at Penn would have a better chance of getting an offer than one at UVA if the actual number of offers given above the GPA cutoff are the same. It really seems like there are a lot of factors to take into account. Purely looking at NLJ numbers or at GPA cutoffs will probably not give you the full story.

Pretty much this. The gap is big enough that it's probably more than just self-selection and class size, but not to the point of being worth $50k.

[Rahviveh]

NLJ may be a good way to determine placement, but it is a pretty terrible way to determine placement ability. The only thing that matters is how deep into a law school class a firm will go, and none of that data for Penn suggests that it has any distinct advantage over MVPDN.

Here's a thread that lays out I'm talking about: http://top-law-schools.com/forums/viewt ... 8&start=25

Here's some better data

Vault V5:
Wachtell | UVa: 2 attnys, Penn: 18 attnys
Cravath | UVa: 8, Penn: 25
Sullivan | UVa: 31, Penn: 42
Skadden | UVa: 44, Penn: 53
Davis Polk | UVa: 26, Penn: 27
V5 Total | UVa: 111, Penn: 165
V5 Per Capita| UVa: 0.31, Penn: 0.68

Non-NY Based Elite:
Kirkland (Chi) | UVa: 39, Penn: 30
Latham (NY/LA) | UVa: 72, Penn: 44
Covington (DC) | UVa: 35, Penn: 23
Gibson (LA) | UVa: 34, Penn: 38
Sidley (Chi) | UVa: 48, Penn: 32
Williams & Connoly (DC) | UVa: 30; Penn: 16
Quinn (LA) | UVa: 15, Penn: 9
MoFo (SF) | UVa: 22, Penn: 25
Ropes & Gray (Boston) | UVa: 24, Penn: 28
Wilmerhale (DC) | UVa: 31, Penn: 28
Keker (SF) | UVa: 1, Penn: 1
Irell (LA) | UVa: 1, Penn: 5
"Non-NY" Total | UVa: 352, Penn: 279
"Non-NY" Per Capita | UVa: 0.99, Penn: 1.15

Penn class size: 243
UVa class size: 357

Unfortunately this ignores the very point I'm making by showing raw numbers from firm bios in place of NLJ percentages. It does nothing to explain placement ability any more than NLJ percentages does and is actually subject to even more variables than the NLJ hiring data.

I've compared notes on CB data with people at Mich, Penn, and Cornell and my impression was they're all about the same, despite having widely different placement stats. The reason it's not already compiled on TLS, I assume, is because schools tell us to keep that data to ourselves. Every T14 2L and 3L should have access to that information for their own school though.

Edit: also, I object to V20 NYC being our benchmark for "prestige." I would assume lots of GULC/UVA students would rather work for a lower V100 DC firm than an NYC V10.

This. It's a little frustrating not being able to share this data on TLS, but I (and quite possibly many others) don't want to publicly distribute this information only to be subject to the fallout that may or may not come with that. I'll admit (this is embarrassing) that the competitive side of me has begun drafting posts in several threads breaking down just how similar Michigan and Penn are based on the average offer GPAs I've seen, but I've had to resist the urge to post this information because it's just not worth proving a point on TLS. If you can get your hands on this data from a friend at another school, I think you'll be quite surprised by (1) how similar the average GPAs are at most firms after accounting for different school medians and (2) how mediocre of a metric the NLJ data is for any single student targeting NYC biglaw.

60k is a ton of money. I know it doesn't seem like it to those of you who are deciding on school, but I beg you to understand that it really is.

This may end up being the best post in this entire thread. I've been on TLS since I began my law school application process, and I started paying my loans in November of this year. As someone who has spanned the full TLS "lifecycle", I can vouch that what once almost seemed like monopoly money when deciding between schools is now incredibly real.

Thanks man, this is great advice. Knowing what you know now, would you say 60k at NU would be better than sticket at UPenn? Are the CB numbers even that similar from 7 to 12?

Keep in mind NW is like 20-30k more expensive than Penn if you believe the COA figures. NW is the most costly T14. So the $ gap isn't even that large in this case.

[JamesDean1955]

.

[HeavenWood]

Keep in mind NW is like 20-30k more expensive than Penn if you believe the COA figures. NW is the most costly T14. So the $ gap isn't even that large in this case.

Which you shouldn't in this case. Apples-to-apples, Chicago and Philadelphia neighborhoods are equally expensive. The disparity in listed COA figures probably derives from the fact that you're comparing Streeterville to University City. The neighborhoods convenient to both campuses vary widely in both cost and quality.

[Cobretti]

Keep in mind NW is like 20-30k more expensive than Penn if you believe the COA figures. NW is the most costly T14. So the $ gap isn't even that large in this case.

Which you shouldn't in this case. Apples-to-apples, Chicago and Philadelphia neighborhoods are equally expensive. The disparity in listed COA figures probably derives from the fact that you're comparing Streeterville to University City. The neighborhoods convenient to both campuses vary widely in both cost and quality.

Noted, but can anyone confirm/deny that NU CB #s are about equal to Penn/UVA?