What Does Your Major Matter? Forum

[FiveSermon]

Always worse than using no data? Then why does anyone use lawschoolnumbers at all?

Is that really how you intend to address my objection? "My hunch is better because lawschoolnumbers is worse than using no data since it is flawed because it is a self selecting sample. It may indeed be accurate and be the best predictor we have but compared to my unflawed hunches and general musing it is obviously inferior hurr durr"

If you missed what I wrote before - you use it for dates, scholarship and such. You can even use it as a flawed individual predictor sure. But what you can't use it is to make assumption on the WHOLE population. The sample that is LSN is only representative of the population that is LSN. You do not use it as a sample of the whole LSAC population. The purpose of LSN would be what they call "for entertainment purposes only/not scientific" (even read the small prints on web polls?).

My hunch is based off of real published numbers - I read the published median/75s and they were lower than B/P and some below. It's a hunch, and I am selling it as such. You also have a hunch, but it is technically "baseless" because you are not considering the whole applicant population (by only looking at LSN which doesn't represent all applicants at all).

So your statements should be qualified as: For people who self-selected into LSN, it seems that CCN is in line with the other people's median ...

So just to prove a point, here is the published medians in question (for all applicants):

Columbia 3.72 / 172................(0, 0)
NYU 3.71 / 172......................(-.01, +1)
Chicago 3.78 / 171.................(+.02, 0)
Stanford 3.88 / 170................(0, 0)
Penn 3.85 / 170.....................(+.03, 0)
UVA 3.85 / 170......................(0, 0)
Duke 3.80 / 170.....................(+.04, +1)

See how LSN isn't worth crap to predict the whole pool?

I am serious, you must not have taken stats. I think the 1st or 2nd chapter usually talks about not using non-random samples and how bad data can mess things up.

I'm confused, are you comparing the law schools' published medians versus LSNs medians? If so, the law school medians would be reflective of those who are attending while LSN's would be of those merely accepted and not those who matriculated. Also, while the data is different, have you actually demonstrated a difference of statistical significance?

Non-random samples are bad, I agree, but the normalization and form of self-selection through LSN should lead to a positive bias rather than a negative one IMO.

Well according to R6, the entirety of LSN is less predictive as a whole than his acute intellectual reasoning seasoned through precious minutes of reading an article which happened to mention something about something...about something...

[r6_philly]

Why don't you go back and read what the original statement you disagree with was? Then think about how you MUST to know the entire population to dispute my hunch. Also I copy and pasted to show BOTH medians and 75s at MVPD are higher than CCN. (then read what I posted again above in the thread)

I worked for a decade modeling data/numbers. There is no point to this debate anymore simply because you think you are right. I have no need to convince you of anything. Let's ignore the topic. This isn't philosophy, a method is either valid or not, there is no "somewhat" valid.

http://en.wikipedia.org/wiki/Sampling_bias

sampling bias is called and ERROR.

[FiveSermon]

Once you land in a school's quartile you're major may start to matter. Harder sciences coupled with good grades in writing are best. While it may not matter so much when you are applying to ls, it may matter when you get out. If you want to do patent law in the biotech industry, semiconductor industry, etc. you will be better served with a degree in a relevant hard science. Not to mention it's very difficult to take the patent bar if you are not a hard science major, it's not impossible, it's just a lot easier.

Moreover, lets not kid ourselves, hard science majors, math majors, quantitative finance majors and the like tend to think of humanities degrees as easy (up for debate whether or not that's true). But hear is a question I have yet to find an answer: would a lawyer who studied hard sciences be more apt to NOT hire a lawyer who studied liberal arts/humanities?

I don't think so. By that point unless you are applying for an IP job, I'd have to say your law school grades matter much more than your undergrad major almost to the point that it dwarfs it into oblivion.

[r6_philly]

Well according to R6, the entirety of LSN is less predictive as a whole than his acute intellectual reasoning seasoned through precious minutes of reading an article which happened to mention something about something...about something...

Yes based a hunch based on 1) published numbers from the entire applicant polulation and 2) 10+ years of professional experience making software used to model and process data.

[NU_Jet55]

Why don't you go back and read what the original statement you disagree with was? Then think about how you MUST to know the entire population to dispute my hunch. Also I copy and pasted to show BOTH medians and 75s at MVPD are higher than CCN. (then read what I posted again above in the thread)

I worked for a decade modeling data/numbers. There is no point to this debate anymore simply because you think you are right. I have no need to convince you of anything. Let's ignore the topic. This isn't philosophy, a method is either valid or not, there is no "somewhat" valid.

http://en.wikipedia.org/wiki/Sampling_bias

sampling bias is called and ERROR.

Cool story bro.

[FiveSermon]

Well according to R6, the entirety of LSN is less predictive as a whole than his acute intellectual reasoning seasoned through precious minutes of reading an article which happened to mention something about something...about something...

Yes based a hunch based on 1) published numbers from the entire applicant polulation and 2) 10+ years of professional experience making software used to model and process data.

You'd be surprised how well LSN fits into 1) published numbers from the entire applicant population and 2) your anecdotal evidence doesn't impress

[sundance95]

nce you land in a school's quartile you're major may start to matter. Harder sciences coupled with good grades in writing are best. While it may not matter so much when you are applying to ls, it may matter when you get out. If you want to do patent law in the biotech industry, semiconductor industry, etc. you will be better served with a degree in a relevant hard science. Not to mention it's very difficult to take the patent bar if you are not a hard science major, it's not impossible, it's just a lot easier.

Moreover, lets not kid ourselves, hard science majors, math majors, quantitative finance majors and the like tend to think of humanities degrees as easy (up for debate whether or not that's true). But hear is a question I have yet to find an answer: would a lawyer who studied hard sciences be more apt to NOT hire a lawyer who studied liberal arts/humanities?

FTFY

[FiveSermon]

Why don't you go back and read what the original statement you disagree with was? Then think about how you MUST to know the entire population to dispute my hunch. Also I copy and pasted to show BOTH medians and 75s at MVPD are higher than CCN. (then read what I posted again above in the thread)

I worked for a decade modeling data/numbers. There is no point to this debate anymore simply because you think you are right. I have no need to convince you of anything. Let's ignore the topic. This isn't philosophy, a method is either valid or not, there is no "somewhat" valid.

http://en.wikipedia.org/wiki/Sampling_bias

sampling bias is called and ERROR.

1. Sampling bias isn't always fatal. If you took stats you would know this. It depends case by case.

2. A hunch isn't even something to consider. A hunch is worthless until you back it up with solid evidence and theory. You have neither. I'm not going to take you at your word just because of your background. That would be silly. Even you admit yours is a hunch grounded in very little to almost no solid proof. All the evidence you have brought up are either irrelevant or obvious truisms.

[spacepenguin]

Well according to R6, the entirety of LSN is less predictive as a whole than his acute intellectual reasoning seasoned through precious minutes of reading an article which happened to mention something about something...about something...

Yes based a hunch based on 1) published numbers from the entire applicant polulation and 2) 10+ years of professional experience making software used to model and process data.

Again, are the differences statistically significant?

You guys are disagreeing on the central assumption that LSN is non-random. By the very nature of it being a sample based on self-selection it IS non-random by strict definition; however, theoretically--and I think this is FiveSermon's whole point--is that self-selected data COULD have zero bias.

[r6_philly]

1. Sampling bias isn't always fatal. If you took stats you would know this. It depends case by case.

2. A hunch isn't even something to consider. A hunch is worthless until you back it up with solid evidence and theory. You have neither. I'm not going to take you at your word just because of your background. That would be silly. Even you admit yours is a hunch grounded in very little to almost no solid proof. All the evidence you have brought up are either irrelevant or obvious truisms.

Now I know why phil majors can't find jobs.

[spacepenguin]

YAY, everyone get petty!

[rman1201]

I can't believe this thread is still going.

Get a good gpa in anything, science if possible.

/thread

[r6_philly]

Again, are the differences statistically significant?

You guys are disagreeing on the central assumption that LSN is non-random. By the very nature of it being a sample based on self-selection it IS non-random by strict definition; however, theoretically--and I think this is FiveSermon's whole point--is that self-selected data COULD have zero bias.

Actuarial science can't work on "could". There is the #1 rule, sample can't have the possibility of being biased.

[FiveSermon]

Well according to R6, the entirety of LSN is less predictive as a whole than his acute intellectual reasoning seasoned through precious minutes of reading an article which happened to mention something about something...about something...

Yes based a hunch based on 1) published numbers from the entire applicant polulation and 2) 10+ years of professional experience making software used to model and process data.

Again, are the differences statistically significant?

You guys are disagreeing on the central assumption that LSN is non-random. By the very nature of it being a sample based on self-selection it IS non-random by strict definition; however, theoretically--and I think this is FiveSermon's whole point--is that self-selected data COULD have zero bias.

I agree with r6 that it isn't a random sample. This is obvious. I don't think anyone can rationally argue otherwise.

What R6 is saying is that because it isn't a random sample it's fatally flawed and completely worthless for generalizing to most applicants. He states this much in his previous points. He goes as far to say that his hunch>LSN when it comes to the entire applicant pool.

What I'm saying is that this isn't true. It is a non-random sample but the error which results from this isn't that great. A non-random sample could have a systematic bias but if that systematic bias is very small then it is still a very strong general predictor.

[r6_philly]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

[r6_philly]

Cool story bro.

That's what I should have said.

[NU_Jet55]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

You are wrong, and you won't admit it. This makes you annoying. Would you consider these insults? Or facts? Just wondering.

[FiveSermon]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

You are wrong, and you won't admit it. This makes you annoying. Would you consider these insults? Or facts? Just wondering.

[r6_philly]

I agree with r6 that it isn't a random sample. This is obvious. I don't think anyone can rationally argue otherwise.

What R6 is saying is that because it isn't a random sample it's fatally flawed and completely worthless for generalizing to most applicants. He states this much in his previous points. He goes as far to say that his hunch>LSN when it comes to the entire applicant pool.

What I'm saying is that this isn't true. It is a non-random sample but the error which results from this isn't that great. A non-random sample could have a systematic bias but if that systematic bias is very small then it is still a very strong general predictor.

You missed the part where I said my hunch was based on population numbers.

You also missed the part where I say we ignore biased samples in talks about the population. Yes it could be representative of the whole, but you don't know the whole, so you have to ignore the sample because you can't test for it's accuracy. Actually, if you have info about the whole population (to prove that the sample is representative), then you wouldn't need the sample.

[r6_philly]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

You are wrong, and you won't admit it. This makes you annoying. Would you consider these insults? Or facts? Just wondering.

I am not wrong. If I am annoying, stop reading what I write.

[r6_philly]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

You are wrong, and you won't admit it. This makes you annoying. Would you consider these insults? Or facts? Just wondering.

I am not wrong. If I am annoying, stop reading what I write.

[spacepenguin]

Again, are the differences statistically significant?

You guys are disagreeing on the central assumption that LSN is non-random. By the very nature of it being a sample based on self-selection it IS non-random by strict definition; however, theoretically--and I think this is FiveSermon's whole point--is that self-selected data COULD have zero bias.

Actuarial science can't work on "could". There is the #1 rule, sample can't have the possibility of being biased.

Have you ever worked with determining insurance premiums as a function of risk/genes? Actuarial science is constantly in the world of 'could.' Either way, unbiased sample>>>>>>>>biased sample. However, there are correcting mechanisms one can implement to 'correct' for bias...just saying.

[sundance95]

LSN may not be perfect, but I agree with the sentiment that some data, even if it is flawed to a certain extent, is better than no data at all.

[NU_Jet55]

YAY, everyone get petty!

I can't help it. Personal insults can only be ignored for so long.

You are wrong, and you won't admit it. This makes you annoying. Would you consider these insults? Or facts? Just wondering.

I am not wrong. If I am annoying, stop reading what I write.

But you post your bullshit EVERYWHERE. Not reading what you write would require me to stop reading TLS completely.



Which, actually, would probably be a good thing. Maybe I should thank you.

[sundance95]

Have you ever worked with determining insurance premiums as a function of risk/genes? Actuarial science is constantly in the world of 'could.' Either way, unbiased sample>>>>>>>>biased sample. However, there are correcting mechanisms one can implement to 'correct' for bias...just saying.

First time I've ever seen "I'm an actuary" used to boost E-peen.