DrFaustus666

My take is, you should either

(1) be a LOT more of a pest to the professor of the class --- FORCE him/her to find a grad student to help you, regardless of how much of a pain-in-the-butt you see yourself to be;

or

(2) withdraw from the class.

Even a "C" in a graduate class, even if that class is not directly related to your major, is widely regarded as a failure. You may still complete your M.S. degree (assuming this is the only "C" on your transcript), but if you ever want to go for a Ph.D. in the same field, at the very least, you'll probably have some explaining to do.

Also, don't let the other students' insouciant attitude throw you. It's YOUR degree, your career, not theirs.

I scored 480-490 on my first few practise tests. I memorised 2200+ words that were totally new to me in two months and ended up with a 740 verbal score. Just sayin!
I also think i've retained about 40% of my new vocabularly. One of my (science) programs at Berkeley plainly said your GRE+GPA is 50% of your decision...for local and international students.

Hey Benzene, sorry to hear this! But you are still waiting for you actual admission decision, right?

Nerves can do crazy things to us (you didn't necessarily say you were nervous, I know). Do you know how people make comments about how they act when they are drunk? Like, "I'm a mean drunk." "I'm a sad drunk." I think we should start making comments about how we act as nervous interviewees. "I'm a cocky interviewee." "I'm a spastic interviewee."

Me, personally, I'm an overly enthusiastic interviewee.

I've done very extensive but informal research on this subject (the scoring algorithm of the computer adaptive test), using the two ETS-supplied Poweprep (OLD) tests, together with lists of the right and wrong answers. I've experimented, deliberately answering a question or two wrong, then answering every succeeding question right, just to see what happens.

The short answer to all of this is: to get an 800 (or high 700s) on both Verbal and Quantitative, respectively, you must
EITHER:
(1) answer all of the first 20 questions correctly, then make no more than two or three mistakes in questions 21-end (30 or 28, respectively)
OR
(2) if you make even one mistake in the first eight questions or so, you must answer all succeeding questions correctly to score above about 720.

Also,
(1) answering all questions randomly yeilds a score in the low 300s at best
(2) answering the first 15 or so questions correctly, plus totally random guesses for the remaining questions yeilds scores in the low 600 range
(3) if you make more than one mistake in the first five questions, it is next-to-impossible to score above 750

All of this is with the OLD POWERPREP program, and of course, ETS has probably improved their scoring algorithm, such that it's not possible any longer to take tons of time on the first 15-20 questions, then rapid-fire guess at the rest.

Hope this helps.
John

catilina,
I believe it. I offer it has less to do with your writing skills and more to do with the fact that there are dozens (hundreds?) of questions in the verbal section and only (If I recall correctly) 1 or 2 essays in the writing section for which there are only two graders each. A relatively subjective grading process that aims to measure something more-or-less intangible based on fewer data points or less information is necessarily going to be subject to greater variability in scoring. I know that the ETS graders follow a certain rubric, but the process of evaluating an individual's persuasive essay is invariably going to be subjective process. Blame the circumstances of testing and the process, not yourself.

Eek! I just checked the website, auto-complete in my browser put the wrong address! Whoops! Guess I am smart enough to be accepted to Princeton but not smart enough to fill out my own damn address...

I've done very extensive but informal research on this subject (the scoring algorithm of the computer adaptive test), using the two ETS-supplied Poweprep (OLD) tests, together with lists of the right and wrong answers. I've experimented, deliberately answering a question or two wrong, then answering every succeeding question right, just to see what happens.

The short answer to all of this is: to get an 800 (or high 700s) on both Verbal and Quantitative, respectively, you must
EITHER:
(1) answer all of the first 20 questions correctly, then make no more than two or three mistakes in questions 21-end (30 or 28, respectively)
OR
(2) if you make even one mistake in the first eight questions or so, you must answer all succeeding questions correctly to score above about 720.

Also,
(1) answering all questions randomly yeilds a score in the low 300s at best
(2) answering the first 15 or so questions correctly, plus totally random guesses for the remaining questions yeilds scores in the low 600 range
(3) if you make more than one mistake in the first five questions, it is next-to-impossible to score above 750

All of this is with the OLD POWERPREP program, and of course, ETS has probably improved their scoring algorithm, such that it's not possible any longer to take tons of time on the first 15-20 questions, then rapid-fire guess at the rest.

Hope this helps.
John

Would you rather spend a year saving money or wasting your time with a degree you won't be using? If you really want to pursue law school, I would say not to continue with a degree you aren't too interested in, just for the sake of not having to work. You might have to pay for yourself to go through school (or partially pay), so why not get ahead and save up some money? Working isn't that bad. It might give you some much needed time to think over your options for the future.

Any decent public admin program is going to require some econ (which uses math), some statistics, and some quantitative data analysis. Math and science programs are not the only things in this world that apply math.

A below-average GRE score won't kill you if the rest of your application is good, but your math score is not just "below average," and I think most social science programs (including those that apply social science like public admin) will see it as a red flag. I suggest doing the paperwork to get your disability documented and get the calculator and extra time, and then retaking.

Hi Secret-Name,

I'm much older than you and it's hard for me to guess what your fellow students (and professors!) might think.

I can share the experience of a former girlfriend of mine, who went to a very prestigious university in Great Britain (either Cambridge or Oxford, I won't say which) -- and dated a professor, marrying him immediately upon graduation (he was 25 yrs older than she).

When they finally made their relationship public, having tried every method known to man to keep it covert,

1. "Everybody" already knew.

2. She did feel ostracized, and one brave-but-forthright student told her directly that for her own sake, she should not date someone in her own field, because "everybody" assumed her superior grades were due to favoritism.

3. Their marriage lasted only two years. She then remained single for 25 years, while he immediately married another student, with whom he'd been having an affair.

Bottom line, amor may vincit omnia, but you'll pay a high price. I think you probably realize that already, but I thought I'd chime in with my former girlfriend's story.

By the way, her marriage to her prof had no effect, positive or negative, on her career.

John

Hi Secret-Name,

I'm much older than you and it's hard for me to guess what your fellow students (and professors!) might think.

I can share the experience of a former girlfriend of mine, who went to a very prestigious university in Great Britain (either Cambridge or Oxford, I won't say which) -- and dated a professor, marrying him immediately upon graduation (he was 25 yrs older than she).

When they finally made their relationship public, having tried every method known to man to keep it covert,

1. "Everybody" already knew.

2. She did feel ostracized, and one brave-but-forthright student told her directly that for her own sake, she should not date someone in her own field, because "everybody" assumed her superior grades were due to favoritism.

3. Their marriage lasted only two years. She then remained single for 25 years, while he immediately married another student, with whom he'd been having an affair.

Bottom line, amor may vincit omnia, but you'll pay a high price. I think you probably realize that already, but I thought I'd chime in with my former girlfriend's story.

By the way, her marriage to her prof had no effect, positive or negative, on her career.

John

I really don't think "if you write more, you get a higher score" is valid. I had 4 or 5 fairly short, well thought out paragraphs, and I got a 5.5. And honestly, there are quite a few times in grad school I've had 45 minutes (or less) to come up with a well reasoned response to something- either a short written summary/response, a presentation, or some combination of the two. And I'm not talking about class assignments here.

But the GRE AW writing section is not to "reflect the strength of a persons analytical writing skill", it's to provide a benchmark of their writing skill under specific conditions (namely, short time constraints & no references).

Weil man Vielsilbigenwörtern schreiben kann, oder?

Your insult only causes me to introspect. I might indeed have been bragging. And I'll admit I was disappointed at my AW score.

Nonetheless, I still think you could have made your original point in a gentler and more constructive way.

Ooh. Hadn't thought of that.

They're both banned now anyway though...

If that's true, I hate ETS. I can't see my essay but my schools can? That's along the lines of how you can't choose which administration's scores to send...you have to send them all. Why don't I just send a naked pic and get it over with? Geeze.

Warning: nerdy and completely useless except as game; if I didn't want to spend a totally unreasonable number of hours engaged in pointless intellectual pursuits, I wouldn't be applying to grad school My math or reasoning in general might be off; if it is; call me on it. Note also that I'm being a Bayesian about things, so read "there is x% of y" as "you should estimate the probability of y at x%."

So, you've applied to some set of schools. For most of them, Peterson's lists their number of applicants, admissions rates, and actual number of attenders from each class. How would one produce an unbiased estimate of your chances of universal rejection (and, possibly, a few other things) from just this information? (Of course if you have more information than this, you would want to make the model more complex to incorporate that extra information, and I'd love to see models that incorporate GPA/GREs, &c.)

a : the number of admissions you will actually receive
n : the number of schools to which you have applied
pi : the admissions rate of the ith school to which you have applied (the order isn't important)

Prior assumption: for the schools for which you have applied, you have no particular reason to believe that you are especially more or less competitive than the typical applicant. This doesn't mean that you expect to be exactly in the middle - if that case you know you would be universally rejected, assuming admissions rates are all below 50% - but that you expect a 1% chance of being in the first percentile of competitive applicants, a 2% chance of being in 2nd percentile or better, a 3% chance of being in the third percentile or better, and so on. If you can accept this prior, your chances of being accepted into school i is, conveniently enough, px, and the average expected number of schools you will get into is

μa = Σni=1pi = p1 + p2 +p3 + ... + pn

or the additive sum of their admission rates. However, you don't know how well these are correlated with each other. If they're maximally correlated - they all admit students on precisely the same criteria - then your chances of a wipeout are equal to the complement of the most favorable admissions rate among your schools; if they are totally uncorrelated, your chances of a wipeout are equal to the multiplicative sum of their complements; if if maximally negatively correlated, then your chances of a wipeout are min(0,1 - μa). Common sense says that they should be positively but not maximally correlated, but how much? Fortunately you know

b : the number of admittances schools in your field send out divided by their number of graduate students per year, where "field" is selected such that its competitiveness roughly reflects the competitiveness of the set of schools to which you have applied

(Sneaky assumption: the number of those in your field you are admitted to grad school and choose not to go at all is zero, or at least small enough to be ignored.)

Thus we know that a randomly chosen applicant in your field - someone, by the first prior, who is as competitive as you - should expect, given that she is accepted into any schools, to get into b schools on average. If, as would be convenient, her expected total number of admittances including the possibility of wipeout is the same as yours, μa, then your/her chances of a wipeout, p(a=0) are

μa = 0*p(a=0) + b*(1-p(a=0))
μa/b = 1 - p(a=0)
p(a=0) = 1 - μa/b

If you haven't applied to the typical number of schools

However, this randomly chosen applicant, who is as competitive as you, isn't necessarily applying to as many schools as you - she's applying to n̄ of them, which might be more or less - although by assumption we suppose the schools she applies to are as competitive as your own. So in fact her expected number of admissions, μā = μan̄/n and

μan̄/n = 0*p(ā=0) + b*[1-p(ā=0)] = b*[1-p(ā=0)]
μan̄/bn = 1 - p(ā=0)
p(ā=0) = 1 - μan̄/bn
n̄ = bn * [1 - p(ā=0)] / p(ā=0)

If we knew n̄, we could know p(ā=0) as well - or visa versa - and thus

p(a=0) = p(ā=0)^(n/n̄)
p(a=0) = (1 - μan̄/bn)^(n/n̄) or p(a=0) = p(ā=0) ^ { p(ā=0) / b[1 - p(ā=0)] }

Can we produce n̄ or p(ā=0) independently? Unfortunately I don't see a way to do so, limiting yourself to the Peterson's data. Choose a number that seems reasonable for one or the other based on anecdotal evidence, or find some publicly available data (and post it here, ideally.) But either way an estimate of one should get you to p(a=0). This should also give you B=μa|a>0, the expected number of schools you get into in the event that you get into any schools at all:

μa = 0*p(a=0) + B*[1-p(a=0)]
B = μa / [1-p(a=0)]
p(a=0) = 1 - μa/B

Revising in light of results

All of the above assumes that you haven't heard back from any schools yet. If you get an acceptance or rejection, how should that affect your expectations of getting into other schools? Unfortunately the ratio of acceptances to grad students doesn't tell us what the distribution of acceptances among the admitted is.

Suppose you hear back from your first institution, University Q - an acceptance. Will you get into another? According to Bayes' theorem,

p(a>1)|into Q = pQ|a>1 * p(a>1) / pQ

Only pQ is a known constant, so we need to guess pQ|a>1 * p(a>1).

pQ|a>1 is the chance that, given that you got into more than one school, one of those schools was Q. This is equal to

pQ|a>1 = (pQ - pQ|a=1) / p(a>1)

so

p(a>1)|into Q = [ (pQ - pQ|a=1) / p(a>1) ] * p(a>1) / pQ
p(a>1)|into Q = (pQ - pQ|a=1) / pQ

(One intuitive, but clearly wrong, estimate of the chance of admittance to Q given only one admission is

pQ|a=1 = (pQ / μa) leading to
p(a>1)|into Q = [pQ - (pQ / μa)] / pQ
p(a>1)|into Q = 1 - (1 / μa)

This implies that an acceptance from one school is nearly as good a signal as a decision from another, and in fact that getting into an easier school should revise your expectations up more than getting into a harder school - prior to learning anything, you have a higher expectation of getting into at least one school other than your reach than getting into at least one school other than your safety, but in fact getting into your reach and into your safety brings their chances to the same level. In fact if there's any overlap between expected admissions at all then the chance of being admitted to an easier program but not a harder program is not only more likely than the reverse, but in a way that exaggerates their independent probabilities.)

One obvious method is to use recursion: imagine someone, as competitive as yourself, who applied to every program but the one you've just heard back from, i.e. μa2 = μa - pQ, n2=n-1,n̄ remains constant, and her field is your field, such that

B2 = (μa - pQ) / [(1- { p(ā=0) ^ [ (n-1) / n̄ ] }]
p(a2=0) = 1 - [ (μa - pQ)/B2 ]

In that case, p(a=0) - p(a2=0) = pQ|a=1, and - if we want to write out a big ridiculous equation -



p(a>1)|Q = {1+ pQ + {(1- [ p(ā=0)(n-1)/n̄ ](μa + pQ)}/(μa - pQ) - p(ā=0)n/n̄ } / pQ


p(I made some sort of obvious arithmetic mistake or worse) > 0.5, so the above is most likely nonsense. If it's right then calculating how to update your chances in case of a rejection should be trivial.

I never heard of Dave Kingman and I'm honest enough to admit it and not google the name first.

What else have I missed?

Or was I too busy onanizing to get your point (my left hand is a little sore actually)?

I agree with coffeekid's feelings. None of the comments were directed at me, but they still hurt my feelings. I also know of many talented and award winning writers who got an insultingly low score on the AW. Well, they still made it into their respective PhD programs. Aren't we all here to offer support and advice to one another?

Yeah. It does. But only we moderators can use it. This thread was mostly contention-free until you showed up. Trust me, your posting ability is in grave jeopardy.

Your insult only causes me to introspect. I might indeed have been bragging. And I'll admit I was disappointed at my AW score.

Nonetheless, I still think you could have made your original point in a gentler and more constructive way.

You lost me.

I get that you're saying I am a bad writer too. But why? On what evidence? I'm not being a pain. I really want to know what makes you remark snidely to me after I chide the other guy for what I see as a snide remark.

Honestly, in good faith, am I missing something?

You lost me.

I get that you're saying I am a bad writer too. But why? On what evidence? I'm not being a pain. I really want to know what makes you remark snidely to me after I chide the other guy for what I see as a snide remark.

Honestly, in good faith, am I missing something?

Your insult only causes me to introspect. I might indeed have been bragging. And I'll admit I was disappointed at my AW score.

Nonetheless, I still think you could have made your original point in a gentler and more constructive way.

Are you seriously being that presumptuous? "[Y]ou obviously lack basic analytical skills... lack cognitive analytical abilities." Well, you obviously lack a capacity for logic, considering the conclusions you make. I know many rigorous analytic writers who have had hiccups on standardized writing exams, and yet they still publish. Why do you think that the ETS offers a re-scoring of your GRE (for a fee, of course)? Because even a pedagogically homogenized organization like them realizes that scoring is inherently interpretive.

I really hope you are just a friend messing with this person... otherwise, good luck making connections in academia with that magnitude of condescension!