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Having the knowledge of a graduate student but not having the degree requirements for graduate school?
Let's say that you're a 27 year old autodidact who has gained enough knowledge in a particular field of the formal sciences - like mathematics, for instance - to be able to take the highest course number from the selection of graduate courses for math.
Now this autodidact wants to enter university for the first time. However, from his perspective, he thinks that it would be a waste of time to restudy what he already knows.
I'm personally wondering if there is a way to demonstrate that he is capable of taking graduate courses so that he could apply for a graduate degree without having to study all the courses at the undergraduate level again.
Also, I'd like to add that this question is really hypothetical. It's just something I pondered on my way to school today.

All it would take is a 30 minute conversation with a math professor in the department.  The mathematical maturity of this autodidact should be clear just from that.

The mathematician Israel Gelfand went straight to graduate study under Kolmogorov without a degree or even finishing high school but such cases are rare.

You are hypothetically a 27 year old autodidact?

If you're asking about graduate school in the US, probably the single most significant thing you can do is to take the GRE subject test for math (not the math section of the general test!), and score well on it. This test covers a broad spectrum of material that is taught in a typical undergraduate math curriculum, and so if you get a good score, it strongly supports your claim that you have the level of mathematics knowledge required to enter grad school. Without that key piece of evidence (i.e. a good GRE subject score), graduate admissions committees are likely to look at your statement that you have the knowledge to take graduate courses, contrast it with your lack of an undergraduate degree, and conclude that you're full of hot air, so to speak.
Now, of course there is more that has to be done to actually get yourself admitted. In my own field of theoretical physics, even a 990 (the top score) on the GRE isn't enough to get you into a good grad school by itself. I would imagine the same is true for the top schools in math, though perhaps at a less competitive school, it might be. But I think to be safe, you should assume that you'll have to present some other sort of evidence of accomplishment that could be viewed as equivalent to an undergraduate transcript. You'll also need recommendation letters and various sorts of essays and forms. But a lot of that can vary from school to school, and is more likely to be negotiable if you talk to someone in the department. The GRE subject score is the one thing you really need to get your foot in the door, so to speak.

If you get a 990 on the GRE subject test in math, send me your scores and I will get you admitted, no questions asked.

@DavidKetcheson Really ? Just according to the result of an standardised test ? I'm assuming that we are talking about a decent graduate program, I don't think we are that much worse.

@onurcanbektas The number of people scoring above 920 on this test in recent years is exactly zero.  See https://en.wikipedia.org/wiki/GRE_Mathematics_Test.

@DavidKetcheson So what ? I wouldn't anyone to score 920 on this test; not even a professor. I mean it not because they are not that much good; it is just because we are not perfect creatures, and we can do silly mistakes, and this does indicate neither something about our knowledge, nor our problems solving skills, or our cabality of conduction scientific research.

Most universities' mathematics departments have placement exams for lower-division math courses, so, for example, you could "test out" of two years' calculus, most likely. Testing-out of upper-division courses is rarer, so there're not going to be formal procedures in place, but if you simply talk to departmental advisors, they can get the ball rolling to have your self-education appraised. It's just that there probably won't be formal procedures in place, due to the rarity of the event. Math faculty are more-than-happy to see someone who's had the interest and motivation to read on their own.
It's not clear that doing the GRE math subject test (nevermind the other parts) is a good avenue for everyone. I'm not such a fan of that exam as a predictor or appraisal, in any case. One aspect is that it is a very superficial exam, in the sense that it tests test-taking ability almost as much as substantitive knowledge, since it is multiple-choice. Second, it presents a very stylized picture of "undergrad/pre-grad" mathematics... unsurprising insofar as it has to be shoe-horned into a timed, multiple-choice exam.
I think it's also not clear whether you should "try to do research" in order to "make an impression". _Being_interested_ and being curious is one thing, but the further element of presumption involved in too-easily believing that with modest preparation one has unraveled mysteries untouchable by experts... blah-blah-blah... will not make a good impression. That is, honest curiosity and drive are unqualifiedly good things, not presumptious, not silly, all too uncommon, ... and are the features the math faculty would look for.
One last small point: it is very helpful to have in mind the authors of the books or notes you've read, whether they're physical books or on-line notes, if only because the titles of most such things are toooo generic, while the best authors are well-known, and the specific virtues of their books/notes similarly so.
In summary: just talk to the math department undergrad-intake-advisors first, and they will steer you to the right people to talk to in order to have your situation  appraised. Some of the people may be a little skeptical, but mostly they will be happy to encounter someone who has the interest who's taken the initiative to study and think about things on their own.

At my university in the Netherlands, TU Delft, there is an obscure clause that says you can just show up one day with a defensible PhD thesis, get someone to act as your superviser, have a defense and be awarded a PhD.  So it theoretically would be possible for a sufficiently dedicated person to bypass all formal university education and still come out with a PhD.

Many graduate programs are geared toward publishing research, much of which doesn't really require the highest-level graduate education to conduct, so if one could achieve a publication record, a history of research experience, or could secure letters of recommendation, that would probably help for certain programs. Getting to know one's potential advisors in advance might also help circumvent some of the usual hurdles (i.e., they might be able to help).

Many graduate programs are geared toward publishing research — "Many"??  Not "all"?

Probably not all, and even "most" would be an empirically falsifiable claim; I have not done the research, so I don't care to go there, and I don't see why it would make any difference if I did.

I'd like to add a few things along the line of paulgarrett's answer, which I'm surprised no one mentioned (unless I just missed it):

This question seems to presuppose that the only value of an undergraduate degree is what you learn in your major courses.  This is far from true.
It is possible to enter undergrad and start taking advanced/grad classes right away.
The curricula at top schools like Harvard or Caltech is a higher level than most people would get from studying on their own.  Sometimes the text for the undergrad courses are the text for grad courses at other schools.  Further, some undergrads at these top schools come in with quite a high level of background already, which makes them completely amazing when they apply for grad school.

(College Level Examination Program) CLEP is the best way, however this only cover the first two years and you'll go in as a sophomore or a transfer.  What i did encounter is that you cannot get a graduate degree with out first having earned an undergrad degree.
Good Luck


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How do graduate schools feel about a student not accepting an offer?
I'm sure it's common for students to reject 1-2 recommendations for admission to a graduate school, because they often apply to several places and sometimes they get accepted in more than one place. But what impression does this give to the graduate school when the student doesn't accept the offer for admission (not sure if this is the correct term)? Specifically universities in Europe where a lot of them don't have application fees. If you apply again in the future, are they likely to not accept you based on this information they have about you from the past? Is that information used at all?
In my case it's admission to a Master's program.
Additional question: if I got accepted to my first choice, would it be better if I told the other universities to cancel my applications?

"If you apply again in the future". You turned them down and you went somewhere else for graduate studies. Why on earth would you apply again?

@Alexandros presumably the OP doesn't want to burn bridges prior to an eventual PhD application.

^ well, yeah it's something like that.

Graduate scools don't have feelings.

Well, I meant professors and people who evaluate applications as a whole. Most likely you said that as a joke, however.

In general, there is not much memory for individual students who act responsibly. Turning down an offer in a reasonable time period is acting responsibly. Initially accepting an offer and not turning it down until the last minute after external and internal funding applications have been made, is less responsible.
I would let departments know as soon as you know you are no longer interested. That means if you have gotten into your first choice school with a nice/fully funded offer, you should turn everyone else down. If you have gotten into your first choice school with a crappy funding offer, you need to decide for the remaining schools what you would do if they gave you a great funding offer. Any school that cannot make an offer that you would accept, you should let know.

I do not have specific information about non-US schools.  However, in the US, the best students generally have choices and are likely to say "No" to a few or perhaps several schools.  It would be silly to discriminate against those students in the future.

What country in Europe?
Speaking for the case in Germany, Master courses are usually "centralized" in the sense that you apply to the university nad not to a single professor. When applying for PhD's you usually apply directly to a professor.
Unless this is about a research master where you are applying directly to someone, I can not see how they would care at all.
It is pretty common to apply to several masters after your bachelors and go for the "best" one.
I would however point that it can be easier to get in contact with your desired future PhD advisor if you are in his university and carry out research projects at his chair, take his classes, etc.

They're in Finland. And yeah, one does not apply to a professor or something like that in the Finnish universities I checked.

It is expected that applicants would most likely have applied for numerious other places so odds are many will turn down the offer. It is very unlikely that HR will remember the individual and hold any kind of grudge against them but if you are really worried, there are data protection laws which ensures that data has to be deleted after a certain period of time has passed (except in exceptional circumstances or where it would still be relevant). Personally, I'd just advise you not to worry about this.

In what country does Human Resources have anything to do with graduate admissions?

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Master's Thesis unexpectedly going south but admitted into PhD program next fall
I was recently admitted into a PhD program, and am currently a MSc Student. Both me and my advisor expected me to graduate this spring, which would mark the 4th semester. Because of that, I applied to PhD programs, and got into a good one. But now I think I might need a bit longer to complete the Thesis portion of it; I could switch to MA which is course based and head on to PhD 1) I am not sure if they will still accept me if I do not have an MSc (the strength of my application was the skills I learned during my thesis) and 2) I want to finish my thesis, because well, I want to publish the results and am interested in it.
What are my options? Many programs do not allow deference, and getting into a PhD program is so hard to begin with.
Thank you for your time.

Probably only the university who have offered you a PhD place can really tell you what your options are.

I don't know the details of your situation, but the conventional advice would probably be:

Pound out a thesis that's good enough for your advisor to let you graduate. It doesn't need to be outstanding or publishable, or include every idea you've considered. It just has to get you the masters.
Start your PhD program on time.
If the project still interests you, continue working on it in your spare time. Stay in contact with your masters advisor. When it's far enough along to publish, do so (perhaps with your masters advisor as a co-author).

To add to what Nate said, explain your entire situation to your thesis advisor. You might be surprised how sympathetic they are and willing to give advice on how to get through the minimum. Unfortunately, a lot of PhD studies is about getting through the minimum.
I have just myself reached the point where I can stop taking classes and focus on my research, but that took almost two years beyond my masters... so basically 4 years of graduate 400/500 level coursework.
First and second years went like this: get excited about classes starting, first week introductions and orientation, gradually become consumed by all the coursework, become a zombie from lack of sleep, taper off and start to question my sanity, then blitz to the end to finish final projects. In my 3rd and 4th years, I was on my iPad halfway listening to the lecture because the coursework was like a programming language: same principals with a different syntax.

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What are the possible causes of a faculty position not being filled?
I applied for a tenure-track faculty position at a particular institution in the U.S. I was selected for a skype interview, but was not invited for an on-campus visit. I snooped around on the department seminar web page, but did not find any evidence that this particular department actually ever invited anybody for an on-campus interview.
Today, I received an email from the department stating:

Thank you for your interest in the faculty position within the Electrical and Computer Engineering Department at the University of [redacted]. Our search to fill this position produced many impressive applicants. However, for a number of reasons beyond the department’s control, the position was not filled.

I can think of a couple of reasons that a department may not fill a vacancy, such as:

the finalists all ended up taking a job somewhere else
none of the finalists could agree to the terms offered by the department

So, besides those possibilities listed above, what are the other possible causes of a faculty position going unfilled?

Possible reasons: they no longer have the funding; none of the applicants matched their criteria.

Most common reason: Everyone offered the position said no.

@JeffE it doesn't sound like OP said no.

At a university here I know a spot once was not filled for gender-equality reasons! The university said they have to hire a woman, but there was just no competent women that applied for that position!

@Jigg: OP wasn't offered the position.

At least at the institutions I know that would bother with Skype interviews in the field of math (i.e. not schools that essentially only hire by invitation), if the first round of on-campus candidates declined, they would just move down the list until someone accepted the invitation of an on-campus interview. With hundreds of applications for each position, it would be unlikely that they could find nobody willing to do that. Of course, things could be different in the field the OP applied in.

I'm addressing the actual stated question — Why might a position go unfilled? — and deliberately ignoring the (plausible but uncertain) hypothesis that nobody was even interviewed. Some departments are very good at not advertising their interview talks.

Not that it matters, but the seminar web page for this particular department listed those job talks given for the previous job posting cycle.

@OswaldVeblen Some schools go down the list only few spots. I heard of a position where 5 people were called for an interview, they moved down the list to #3, and after they declined they decided it might be better to reopen it at a later time.

I knew of one relatively small department with 2 long-term unfilled positions.  It turned out that the three tenured faculty had significantly divergent opinions on hiring and were essentially waiting for someone to die.  That deadlock ended in an attempted murder and successful suicide.  One of their postdocs...wasn't surprised.  Politics in top-ten universities can be surprisingly inefficient.  To be fair, hiring everywhere tends to have 'quirks'.

You will probably never know the full reason, because departments are not quick to air their internal issues with job candidates. But here are a few possible reasons:

The search was halted by higher administration. One possible reason to do this so late in the process is because of funding changes (e.g. the funding for the position disappeared or was reallocated elsewhere).
The search was halted by the HR department due to some violation of hiring practices.
The search committee was unable to come to an agreement about who to bring to campus for an interview, or the dean rejected all the candidates before they were interviewed.
Although this is less likely, someone who had planned to retire might have decided not to retire, or someone from another department may have been moved into the department (e.g. for legal reasons to settle a complaint).

One more reason (perhaps related to #1 on your list): A totally unrelated search in another department brought in a senior candidate with a trailing spouse. The hiring of that spouse meant that a slot was lost in the grand shuffle.

There were lots of instances of #1 in the 2008-2009 hiring season.  When the financial crisis started getting dire in fall 2008, endowments and state budgets dropped, and many schools instituted hiring freezes and canceled searches.

There may have been a change of administration in the middle of a search, and the new administrator didn't like the position description posted.


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What do IEEE journal prefixes mean
I found that IEEE journal names have prefixes, the most prominent I observed:
IEEE Transactions on...
IEEE Reviews in...
none specific (starting with IEEE)
Do those prefixes suggest the eminence of journals?
I apologize if this is something trivial, but I struggle to find some reliable explanation regarding this issue. Understanding the nuances in the journal naming system would help me better categorize and search journals that suit me.

As with any journal, the name is only a weak indicator of the content (since they often have a long history spanning multiple editors-in-chief, who do the most in shaping a journal). Instead, you need to look at the editorial policy (sometimes called scope) of each journal to decide where to submit your paper.

I apologize if this is something trivial, but I struggle to find some reliable explanation regarding this issue. Understanding the nuances in the journal naming system would help me better categorize and search journals that suit me.

There is no reliable way to use the name to conclude about the eminence of a journal. There are some heuristics, though:
IEEE Transactions are typically supposed to be the flagship journals for a broader field. Quality between different transactions varies, but from the top of my head I cannot think of an IEEE transactions journal that is really bad.
IEEE magazines (IEEE Software, IEEE Internet Computing, IEEE Computer, etc.) are also mostly very well-respected, but their scope is entirely different. They publish short papers written for a broad audience. They are heavily copy-edited (for instance, the copy editor will typically re-draw all figures in a common style across all papers in an issue), and they tend to have a large impact (because these magazines are circulated very widely). However, due to limited size, they are often scientifically more shallow than transactions papers.
Other journals, that fall into neither category, vary in quality and esteem (though they are typically weaker than the relevant transactions in the field). Their scope is typically more narrow than transactions, but the opposite can also be true.


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Is it good practice/advisable to sum up passages from a reference into a few sentences in my own paper?
Of course, I would retain the for me important points, but omit the details.
To the question in the title, I would like to add: If it is, how would it be best to point to that paper?
Should I reference this as a "regular" citation or is it better to include some explanation, like "From [5] it is clear that ..."?

Could expand more on the kind of explanation you want to include? I would not call "From [5] it is clear that ..." an explanation.

Also, "[5]" is not a noun.

@JeffE: You'll think I'm being sarcastic, but...I think it is of some philosophical interest whether your previous comment is in fact true.

@PeteL.Clark: I agree, although I'd say rather that it's of linguistic interest.  Maybe "[5]" is a pronoun?  Whether or not the quoted is phrase is grammatical, though, there's the separate question of whether it's good academic writing.

Whether it's good, grammatical, or otherwise, it is very common.

I would agree with @MarkMeckes that "[5]" could be considered a pronoun, since it substitutes the reference to the source in question (title, author(s), publisher, year, page, etc.). As of its use in academic writing, I've used it and I've seen many others who did, but I certainly can't claim that I'm an expert on those matters. However, I think it makes sense, because it keeps the notation short, concise and consistent; the title of the source is often very long and the author(s) may have other works that are cited in the paper, so that may not always be unambiguous.

I know people who restate whole proofs of mathematical theorems, either because the proof itself is interesting, or simply because the original presentation of the proof is poor in their opinion.
It is completely fine to summarize works of other people in your work, you just have to make it completely clear that it is not your work. But you can quote even whole paragraphs IMHO, without much problem (surely in math/natural science, I'm not sure how's it in philosophy and such).

I think there is no problem to sum up informations if they have been investigated already. You should reference this as a normal citation.

"From [5] it is clear that ..."

It's better to write the title or the author's name (or research group) instead of reference number. If you take informations from a book or the like, you can use something like 'It is well known that... '


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Some results of my grad research have been used in a recent paper, but I was not told. Should I do something about it?
Some of the work I did during my undergrad research (before my PhD, 4 years ago), exactly two figures, have been used in a recent paper. My ex-adviser (at the time of my undergrad research) is co-authoring the paper but she did not tell me about it. We kept being in contact after my undergrad research and we had planned to write a paper, then I started my PhD somewhere else and it did not succeed.
As I keep having good relationship with her, I don't know if I should do anything about it.

Indicate in the question whether a citation to your work was given.  That information can significantly affect the answer.

You should have been cited, at least, if the old figures were used and you created them. There may even have been a copyright violation here as figures are sometimes (often?) considered to be a "complete" work for such purposes.
You could ask for an explanation. You could express disappointment for the lack of acknowledgement. I can't predict the outcome, however. It might be an apology. It might be rage. What should happen is a correction, but that doesn't seem very likely.
I'm assuming, of course, that the figures really were re-used, rather than just being similar and generated from the same data.
But you have to judge whether to rock the boat a bit. It is your right to do so. If you need her as a source for your future advancement, then tread carefully.

Actually, one figure is the exact same, while the other was augmented to include more data in time. Co-authorship or IP rights are not a problem either, as I consider that my work is free to be used. My reaction is more related to the fact that we could have published a paper together, but instead of that some of my work was used in a different study, which I regret. Thanks for your answer.

From my point of view this depends on how substantial these figures and the work you put into them were. If these are standard figures that I'd have done myself anyway, or figures I had encouraged the student to do, I wouldn't feel bad about using them in my publication, at least after it's clear that there won't be a joint paper about this work. I'd probably still tell the student in advance that I plan to do this and mention the student in the Acknowledgements, however I don't think the student can claim an "intellectual right" on such things.
If it was your idea to do these figures and there's some of your own original thought and proper research work (on top of doing what you had been asked to do) in them, the situation is different. However in this case I agree with the answer by Buffy.

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Do professors need to use up their grant money in a fixed period of time?
Just curious, do professors need to use up their grant money in a fixed period of time?
Or can they reuse the left over amount for other projects?
What are the incentives for them to use grant money as opposed to "saving" them?
Thanks.

That depends on where the money comes from, but in general yes, they should use it. Just like everywhere else, budgets are tight. And if the money is not fully used in a year, the funder might assume that this professor can do well with less money, so the next year the funds are decreased. I witnessed a case a few years back where a professor decided it was time to get a fancy notebook for conferences in mid December, because there was still money left...
Another possibility is that some other institute/chair/professor puts his hands on the money if the professor does not keep a tight eye on it. I myself got asked once to "please move to this office for a few months, as if we don't occupy it, it will get redistributed to another institute and we will then never get it back".
Same might go for teaching assignments, e.g. a math chair teaching basic calculus to engineers, economics,... might be a source of income fought for.
These are of course only examples and there might be cases where saving it is possible (so feel free to wait for more answers), but from these experiences I am fairly certain that using the money is the better choice.

The NIH almost always offers the ability to roll money from one year to the next and then at the end of the funding period a no-cost extension.


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Importance of publications if one decides to go industry after PhD?
If a PhD student (hard sciences like math, physics) decides to work in industry after graduation, are publications important?
For transition to industry, what are the most important factors to take note of during one's PhD?
Thanks for any advice.

In computer science, I was advised, by several people, to remove my publication list from my CV. Matter of fact, the whole structure of the CV is different. While they may consider the publications at some point, it seems rather secondary...

By "work in industry", do you mean one of the few industry research jobs directly connected to your area of PhD research, or something requiring some technical knowledge but not particularly connected to your PhD, or something with no specific technical requirements at all (but for which the general skills you gained doing a PhD are likely to still be helpful)?

@AlexanderWoo I mean something like data scientist or quantitative finance for instance, which may not be related to PhD.

Publications demonstrate several things such as:

Ability to conduct, complete, and document work
Ability to communicate clearly
Interest in broadening the field's knowledge
Interest in staying aware of the "state-of-the-art"

All of these are good attributes to demonstrate with a publication record.  Continuing to publish in industry is also valuable, but it is seldom "publish or perish."
Regarding important factors: use elements of your Ph.D. to demonstrate that you can work independently to solve difficult problems.  A strong work ethic and ability to solve problems are key traits that employers are looking for.

This answer is not wrong, but I feel it somehow fails to point out the difference between "publications" (a few examples of published works in any kind of research or otherwise venue, showing that the applicant is capable of the points described in this answer) and the "publication record" (the full list of publications, each indicating the research publication type, showing that the applicant produces a steady stream of publications in somewhat prestigious research venues year after year).

For transition to industry, the important factor will be the ability to quickly convince the potential employer that you're the best person for the specific job. Which typically means you have to tailor your resume/CV to each employer.
Keep in mind that a potential employer typically have to go through many resume/CV within a short period of time. The person deciding which candidates should be shortlisted for interview may not be familiar with your research area. There may also be several candidates with PhD from different areas applying for the same job, along with a number of candidates with experience in the type of work similar to the position being advertised. So simply listing all your publications isn't helpful.
Instead, try to explain how your research experience makes you the best choice. Emphasize some of the research experience or publications that are quite relevant to the position. For example, if you're applying for a job as data scientist at an e-commerce company, and you have publications related to, say, automatic mining of customer opinions or automatic discovery of substitute/complementary product relationship, then it may be good to mention and emphasize that as evidence of your suitability for the job.


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Being asked to pay penalty if fail PhD qualifying exam
Just to ask, how common is it for universities to ask a PhD student (fully funded) who has failed the qualifying exams to pay back partially or in full their stipend?
I heard some anecdotes that some universities require students to pay the equivalent of masters course fees in order to graduate with a master degree. This is supposedly done to deter students who enroll in a PhD to get a free Master by deliberately (or otherwise) failing their qualifying exams.
Thanks for any input from any professors/ students inside or outside US!

You can never say never, but to "hear" about students deliberately failing their qualifying exams in a cunning plot to get a free Master should be an urban myth. While you can put anything in a legal contract, it doesn't mean it is enforceable. I genuinely doubt that an agreement to pay back a stipend because of failing an exam would be in the U.S.

Deliberately failing exams because a new try at a later time (with a possibly better grade) is preferred over a just-about-passing grade happens (and is, by the context in which this happens, completely legitimate within university rules), but I fail to understand how failing could lead to a "free" degree.

@O.R.Mapper The only interpretation of "free" that I can think of is that, by being a Ph.D. student, one can get funding that one could not get as a masters student. So honestly applying for and getting a masters degree costs money, whereas pretending to be a Ph.D. student, failing, and getting a masters degree as a consolation prize does not.

@AndreasBlass: Oh, ok. I thought of "free" in the educational sense (i.e. without qualifying by virtue of passing exams and the like); didn't think of the places where there is a monetary aspect to it, or where a Masters requires similar funds as a PhD. While your explanation sounds reasonable, I wonder whether the qualifying PhD exams wouldn't be at the beginning of a combined Master + PhD programme, rather than after all educational requirements for the Masters degree have been fulfilled. This would make sense if, as would be the case, enrolling for a Masters and enrolling ...

... for Master + PhD is not administratively the same during the Masters phase.

Yes, by "free" I mean in monetary terms since most PhDs are funded while master students may not be funded

In the United States, I have never heard of such a policy, and would consider it somewhat strange and vindictive on the part of the university.  Yes, it can be frustrating for professors when a student drops out with a Masters, but it's better to lose an unwilling or unable student early than to attempt to cudgel them along toward an ill-deserved doctorate.
In terms of "free rides" and "paying back," in most cases that I am aware of, a Ph.D. student who is supported by the department or their advisor is not just given money, but is working as a teaching assistant or research assistant.
Perhaps if one was supported by an external fellowship it might include such a term.  If I were a student, however, I would be very leery of accepting such an offer.

This is right on target.  Some programs are designed to be flexible and allow for an exit with either a Masters or a PhD. Others are intended to lead to the PhD, but even in such a case, if things are not going as well as hoped, the department is happy to cut its losses and give the student a Masters and let everyone part ways gracefully.

Exactly. The purpose of qualifying exams is to screen out those students who are going to be unable to complete a PhD before they waste enormous amounts of their and their advisor's time. (Maybe it doesn't always succeed at this, but that's beside the point.)


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Letter of recommendation from professor who is not longer at your university
I am applying to graduate school in US for MS and Phd program. I wonder is it a good idea to ask for a letter of recommendation from someone that I took his course and I did amazing in his class and he knows me very well but he is now professor at another prestigious institute ?

It's not just a good idea, it's an excellent idea.  Your professor is still in just as good a position to speak to his experience with you and his assessment your abilities as he was before.  You say he has moved to another good institution, so there is no reason for his opinion to be discounted just because he moved---changing institutions is not unusual.  In fact, if he is happy to write you a good letter, it will look even better than if he was at the same institution, because even after changing institutions he still remembers you and cares enough to write.

It doesn't matter where the professor works now, but you should state clearly that the professor once taught you at your university.


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Can I ask a lecturer for letter of recommendation
I wonder can I ask a lecturer who I took his course and I did amazing in his class for a letter of recommendation?
The reason why I am asking is because lecturers are not usually doing research and might be permanent faculty member.

It might be helpful to specify which country you are in.  In the UK and in countries with similar university systems, most lecturers do research.

If you're applying for a research-based position, it is almost always better to have letters of recommendation from people who know you and can comment on your research skills.
However, if you do not have enough letters of recommendation that can come from such people, then a letter of recommendation from someone who knows your work well and can comment on your strengths and weaknesses is also acceptable—even if it is not a "permanent faculty member."

I think you mean "tenure-track faculty member".  In my experience, most lecturers are de facto permanent, even if they don't formally have tenure.  And in many US universities (like Berkeley) some lecturers do have tenure (or "security of employment").

I was quoting the OP in the use of "permanent."

Thanks for your answer but based on what you say if I need 3 letter of recommendation then I need to work with at least 3 different faculty advisor and therefore 3 different research labs.

@user59419: Yes, ideally, you would have three such distinct letters from research staff—professors are ideal, but it could also be from a research scientist at a company or non-academic lab. If you don't have three, then look for recommendations from teaching staff. (A good letter is a good letter, but a good letter that can comment on your research aptitude is much better than one that doesn't.)

If a lecturer can comment your relevant skills, then there is nothing wrong with asking a reference letter.  As your instructor, they may know that you are highly motivated, hard working, easily grasping the hard theoretical concepts... all very relevant for e.g. grad school.
In my experience the problem is more often that the instructor does not really know you.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Is really PhD necessary for someone who wants to work in industry
I am wondering if my goal is to work in an industry as an electrical engineer, is it better to get PhD? I know PhD might open some options for me such as working in industry and teaching in academia at the same time or research job. However PhD is a long term commitment and during this time you can gain a lot more experience by working at a company and this will be considered as a professional experience, which may be more useful.
I would like to know what do you guys suggest? is it worth it to spend 5 years and obtain PhD?

[is it worth...?]; you should answer this to yourself based on your goals and life condition. If there was a unique answer to this, we may had no PhDs currently, or all the people may had a PhD degree.

I'm voting to close this question as off-topic because it's about a career in industry.

Although I think the linked possible duplicate question above could be a very valuable resource for you, to answer your question: no, a PhD is not required to be an EE in industry. I did so for about 10 years without one.

The title of your question is rather starkly phrased.  Since most electrical engineers working in industry do not have PhDs, clearly a PhD is not "really necessary".
There have been a lot of questions asked about this on the site already, which you may want to look into.  In the absence of more specific information, one can only answer in general terms.  What I would say is that PhDs are first of all for people who want academic careers and second of all for people who have a good, specific idea of what non-academic career they want and how the PhD will help them with it.
If your goal is to work in industry as an electrical engineer, I would try to realize that goal as soon as possible: i.e., as soon as you have a bachelor's degree in electrical engineering.  Then you can find out whether you really like it, get experience and so forth.  You'll have a much better idea of the pros/cons of coming back for a PhD after spending time working in the field, you'll have plenty of people to ask about it, and you may even get financial support from your employers (so that for instance you may not need to do the teaching and grading that other grad students will, though as I type this I realize I don't know how much EE grad students teach or grade).

Good advice -- get your feet wet.

I think it heavily depends on the kind of industry you are working in. In biotechnology for example, people with a PhD are more likely to get a job in research. In heavy industry,especially in production, you are going to meet much more engineers ore people with a master degree.


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Can low score in GRE hurt the application with good GPA for top graduate school in US
I wonder can poor general GRE exam hurt an application with very strong GPA (about 3.9) and good letter of recommendations for getting an admission to top graduate schools in US? meaning that How strong is effect of GRE ?can you be rejected based on your GRE result?

What program are you in?  In STEM disciplines, a low quantitative GRE will usually kill your application.

In Engineering program. How low will kill the application?

That depends on the school.  But the mathematics that you need for graduate-level engineering is usually well above what the GRE tests.

Like @DavidKetcheson said, it depends on the school.  But because advanced engineering requires quite advanced mathematics, anything under 160 will probably raise red flags.  You might be able to prop up a score between 155-160 with other really good "fundamentals", but most students in top-level advanced engineering programs are scoring 165+ (http://magoosh.com/gre/2013/gre-scores-for-top-universities/)

For those of us who are more familiar with the 200-800 score sheet, ETS concordance places a new 160 score at a 78%ile. A 155 is 60%ile, falling into the average student range.

I am not in engineering, but chemistry, and I suspect the answer is very similar.
I won't lie. This will definitely hurt your chances, depending on how low your score is.
For one, many programs have minimum GRE scores for acceptance - that may or may not be advertised. There are so many highly qualified applicants to top schools that the admissions committee have to do something to cut back the pile. While there are advantages and disadvantages to the GRE, it is standardized and using a score level as a filter is helpful to the committee. (Usually this "first cut" is a GRE score well below the average admitted score. We know that some students don't test well, so we'd prefer to look at the whole package.)
Beyond "your score is too low," let's assume you make the first cut. At that point, the GRE matters less, since the committee will read your recommendation letters, look at your transcript etc.
Even then, the GRE matters some. If we're considering a student coming from a school that we don't know, we simply cannot calibrate the GPA and/or the recommendation letters. So the GRE gives us some information on what a 3.9 GPA "means" relative to another student at a school that we know.
Finally, the GRE is a piece of information to the admissions committee. One key thing it tells us is how seriously you took the exam and whether you prepared for it. We know that the GRE is a self-selecting bunch. You only take the exam if you're considering applying to graduate programs. So if someone gets a very low score.. well, that's not a good sign. What do we learn about how serious a student will be in grad school?
All that said, I have talked over the years with colleagues in other departments and other schools. There isn't a huge correlation between GRE scores and success in graduate school. There just isn't really anything better either.


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Professor asked me for draft of letter of recommendation,what should I do?
I know there are a lot of discussions about this topic in this forum and I read all of them but my situation is slightly different.
I took a class with my professor and I worked in his research lab and I know him for a while. When I asked him for a letter of recommendation he told me send you CV plus draft of your letter of recommendation. In this forum a lot of people said do not do that it is unethical. I understand this and I understand why it is unethical but what should I say to him should I say this is unethical and I cannot do that or should I forget about letter of recommendation from someone who I worked in his lab.

You might tell the professor that you feel uncomfortable writing a letter for yourself, but that you'll be happy to provide the CV and a list of the things about you that you would be happy if they emphasized in the letter.

First, I think it's important to get this letter of recommendation. Letters coming from professors who have first-hand experience of your research experience are incredibly important in STEM fields.
When it comes to getting strong letters of recommendation, I generally advise students to submit their CV and a comprehensive list of what they did in lab from start to finish. I would keep it to a page or less and include class work, but this is standard at my University. It sounds like this professor just wants the letter-writing process to be easier for him or her. Letter writing can be difficult, and these two items make it significantly easier. If it were me, I would go forward almost as if he didn't ask directly for a draft.
You also might ask for advice from another professor in your department. Professors are known for their quirks, and I'm sure you aren't the first to notice this professor makes unusual requests. I would make sure that you can trust the faculty you ask for advice, but you would be surprised at the quality of the advice professors have for dealing with other faculty.


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Should I include name of potential advisor on my statement of purpose (SOP)
I am currently writing my statement of purpose (SOP) for top graduate schools in engineering majors in US. I am wondering should I include name of my potential advisor on my SOP (Is it a good idea to do that)? The problem is I am thinking if I do not include name of advisor it might be the sign I did not look at his/her research page and I am not very specific about my plan. On the other side, if I include name of potential advisor and my application is not competitive or he/she is not accepting any graduate student this might cause others not to look at my application since they might think I am not interested in their research.

Faculty at a top-10 school in aerospace engineering gave a former student of mine the advice of indicating several professors whose research he was interested in, for exactly the reasons you suggest: by showing too narrow a scope, it makes it harder for other researchers to gain interest, and by just submitting a "generic" SOP, you run the risk of looking like you're not doing your homework. Showing an interest in several faculty makes it easier for someone to advocate for you in the admissions committee.

Do you think including name of three professors in statement of purpose is bad and cause graduate committee to believe that we are not specific enough about our plan?

You're allowed to be uncertain about exactly what you want to do as a graduate student. So long as you have clear reasons for why you want to work with them, it should be fine.

I think it's standard to list some potential advisors.  It shows you know what you want and you have a good reason to be interested in the school.  And if none of the advisors you want are taking students, do you really want to attend the school in the first place?
(In the long run I think it's better to get rejected from a school than to go there and realize there's no one there who wants to work with you who you would also be willing to work with.)
I would also go into some detail about the area of research you are interested in.  This is a good chance to display your familiarity with the topic/maturity as a researcher, and it will help them assess whether they have spots for you.


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What factors determine acceptance to top graduate program in Engineering?
Question that is really bothering me is what are the important factors for admission to top five engineering graduate school? I searched in different forums and saw people got accepted to  PhD program at prestigious school with GPA 3.40 GRE Quantitative of 165 and no publication. However I also saw people could not get in to even master program with 4.0 GPA ,good GRE score.
I am starting to think that GPA ,GRE and even research experience are not determining factor. Can anyone please clarify this for me?

searched in different forums and saw people got accepted to PhD, Do you personally know them? How do you know those are true stories? Here say, there say. Use whatever you see online as reference, not evidence. Do your best and get good recommendation letters. That's what you can do.

To get into a top graduate program, you typically need:

No red flags that will cause your application to be discarded.
Something that causes you to stand out from the vast crowd of good applicants with no red flags.

A lot of people seem to think that having an extremely high GPA, GRE, class rank, etc. will help, but it does not.  The problem is that such standardized evaluations address only category #1.  There are a lot of good students out there, and graduate programs aren't really interested in whether you are the best student.  Instead, they are interested in whether you have problems as a student that would prevent you from succeeding in graduate school.
The honest truth is that there is a huge amount of unpredictability in satisfying criteria #2. and you can only do so much to control it.  There are many useful things you can do to help make yourself stand out, like participating in research projects, but ultimately there are no guarantees, because you never know how many other excellent candidates might also be applying to that program in that year, and what exactly it is that will make one person's application resonate with the particular faculty member who reads it.

I applied to, and was accepted at well know university after attending a small regional state school.  While I have no proof of this, I sincerely believe the quality of the letters of recommendation is what made the difference.
I had a 3.5 GPA and good, but not great GRE scores, and no papers.  I was heavily involved in the ACM (computer science professional organization), and signed up for several grad level classes.  I made sure my letter writers would have more to say then "is a good student."  Show that you are truly passionate about your field of study.  That will be reflected in recommendations.

An important factor is where the student did their undergraduate work.  The admissions committee will be familiar with many undergraduate institutions that have good reputations and some that have bad reputations.  If you come from an undergraduate college that has a bad reputation or that the committee is simply unfamiliar with, then this will make admitting you a risky choice.  If there are plenty of strong applicants from well known good undergraduate programs, then the easiest thing to do is to select from those students.

Is it usual that an undergraduate student in USA has published by the time he gets his degree BSc.? I really doubt it. 3 - 4 years is quite a short time for a student to equip himself enough to write anything meaningful. In Europa, a 5-year Master program (3 + 2 years) may probably last 6 - 7 years, because the Master thesis is a relative heavy project. People may even need a year to plan, set up and conduct experiments in the laboratories. After that they could spend several months on writing thesis, rarely one has publication.


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Should I talk about my PhD acceptance in follow up email to potential advisor in different school
I got accepted in one of the top-tier school in US for PhD program in Engineering however my dream is to go to different graduate school. I am planning to send a follow up email to one my potential advisor. Can you please tell me how to start and should I mention that I got in to PhD program in one the top-tier school? Should I start with as we talked before or as I mentioned in previous email?

What is the goal of the email? Is the goal only to inform the advisor that you got into that school or do you want him to do something?

I would like to ask him/her that whether she/he has looked at my application ? what is my status of my application.

you've already contacted him/her previously and verified that he/she is accepting new students, correct?

Yes. That is correct

No.  You will appear to be threatening to go elsewhere if they do not act on your application soon.  People may react to such (perceived) threats by saying, "Don't let the door hit you on the way out."
If the other institution has a deadline by which you must accept their offer, tell your chosen school, "I really want to come to [chosen school] but other factors require me to make a decision by [week before deadline date.]  Is it possible you could help with that?"


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Is it good to label papers as Part I, Part II?
If a paper is too long, I was advised to split it into two papers. What is the general opinion of reviewers/editors on having "Part I", "Part II" literally in the title of the papers?
Or is it better if I replace "Part I", "Part II" by more descriptive titles?
Thanks. (My field is in Math.)

Did you contact the editor of the journal? If you are having a longer proof, they might have procedures for that.

There are quite a few famous papers in CS called "Foo bar bizzz, Part I" with no Part II.

You can do that, though a better approach may be to title them something like

Hypersingular monoids in graph theory. Part I: Definitions and basic properties

and then

Hypersingular monoids in graph theory. Part II: Applications to semiregular smoothness theory of spiked stars

This way, you're a bit more expressive than just part 1 and 2.
The downside of this approach is that good journals will ask you to make sure that either "Part I" is already self-contained and of independent interest (which is probably difficult to achieve if you are currently splitting up something you've already written), or that you submit the two parts together (so that the combined oeuvre can be reviewed as a whole). The latter, of course defeats the purpose of splitting it in the first place.
Long papers are a hassle all around. It's difficult to get them through the review process, and much depends on what concretely you have in the paper(s). As a consequence, there is little that can be said in terms of specific advice in your situation without knowing the details of the paper. Talk to some of the experienced people in your field about the situation and ask them how they would suggest you handle it!

Actually please, please add the "part I" and "part II". I have seen a few papers which are clearly part 1 and 2 to each other, but have not be named as such and now it is easy to find only one in literature search and miss the other part which might have had the information you actually needed. It also reminds me to be cautious about not mixing them up.

This keeps happening for a lot of people. Why don't you split it into different titles? What I mean is, try publishing the Part I and then publishing part II as an extension of part I. This has a huge advantage. Plus you get a citation.

This does not seem to actually answer the question, which is about whether to name the two parts as I and II or similar.


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Is applying to 20 graduate schools too much?
I am applying to math graduate programs, have a list of schools of different range, but I am so worried about being accepted to a grad school, that am considering to apply to 20 schools.
My undergraduate institution is one of the top schools in math, #1 or #2 in several math fields.
My worry is that I messed up grades of some important classes, also totally messed up my gre sub, since I didn't prepare for it at all. But I do have lots of research experience in fields related to applied math (I want to do applied math, now I am pure math major).
Should I apply to 20 or there is no point in applying to so many, maybe just 15? I also don't want to disturb my rec letter writers so much.
I am not thinking about the money I have to spend on the application process
Thank you :)

I don't teach math so I have no idea what the norm is. I have seen a colleague (biomedical) on full rage because some student needed 12 recommendation letters. I wrote 7 recently for one student and I was on the verge of crying. I guess you should at least give the reference person a heads up and test their tolerance. And don't bait and switch, if you contacted them for 8, don't up it to 20; you don't want an unhappy person to evaluate you when checking those multiple choices.

Are there really 20 schools that you are seriously interested in applying to? How far down your list of "safety schools" are you going?

@keshlam not really, especially the last 5-6 schools I picked were mainly because of my worry of not getting into any of the schools I apply to, not because I actually want to go there, which is not good considering I'll be spending 4-5 years of my life there. I will narrow down the list to at most 14-15

Sometimes the right thing to do is apply to the set of schools you actually want, see if you get in, and if not spend a year working at something that will improve your status as a candidate and apply again. Worked for me.

I have also been considering applying to internships and working in a science related field for a year, then applying if it doesn't work out this year. So in the end I guess no point in applying to so many. Thanks for the advice @keshlam!

@Penguin_Knight: Do you really write different letters for every school to which the same student applies?!?

@PeteL.Clark, where in my comment I said the letters are different? To answer that, yes. Some schools ask for a bit different criteria so I had to twist the structure somewhat. That is not a big deal. And what drive me to crazy is the different systems and online evaluation forms that I had to go through. I just cannot imagine doing that 20 times.

If you don't get accepted to any of them, then it wasn't. If you get accepted to all of them, it was. If you get accepted to 5 or 6, then you have choices, instead of being pigeon-holed into one choice.

Just my opinion: Do you really need to apply to 20 schools? I think it is very hard to be focused when applying to many schools. You also have to spend lots of money, and more importantly, you have to find referees willing to write 20 recommendation letters!
I have read many articles and most of them suggest 6-8 school: 3 reach schools, 2 match schools, and 2 safe schools and that seems reasonable.
20 seems to be too much and a waste of your time and money.

If you are worried about being accepted narrowing your choices would be better than enlarging them. Focus on the ones you think will be more successful.
Despite you messed up some grades your researching experience should be taken into account.

I also don't want to disturb my rec letter writers so much

You'll definitely disturb they by applying to 20 schools.

Welcome to Academia SE. Note that we are not a discussion forum and if you agree with an existing answer, you can and should express this by upvoting that answer (which you can do as soon as you have sufficient reputation). As it stands, your answer adds nothing to the existing answer.


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How to format citations for proposals with a 5-page limit
I’m submitting a proposal that has a 5 page limit (12 point font!) for EVERYTHING (figures, citations, tables) and I’m wondering how best to format my citations to save space.  No specified citation format is given.
What I’ve tried to do is abbreviate common words, use initials for the journal titles (I provide a key), drop “19” and “20” from the year, and pile everyone after the 1st author into “et al”.  In some cases, I’m dropping words, eg, if they come after a colon.  My goal is to provide enough info to indicate what the paper is about and that it could be found using Google.  I put it all in 2 columns.
I’m worried that this is getting ugly  and that I might annoy reviewers that are used to a certain format.
What I currently do:
3)Doherty et al. ‘02. Surv. of resident birds in a frag. forested landscape. Eco 83.
4)Lawson et al ‘15 Env. variation and pop. responses to global change. EL.
One option is what Science uses, eg
D. G. Ainley, L. B. Spear, S. G. Allen, Mar. Ecol. Prog. Ser. 137, 1 (1996).
But I’ve never liked this b/c the title gets completely dropped.
Another options would be to glob everything together like this
1) Barraquand et al. 2013. When can env. variability benefit pop. growth? Counterintuitive effects of nonlinearities. Theor. Pop.Bio 89:1–11. 2) Black et al. 2012. Stochastic formulation of eco. models & their applications. TREE 27 3) Bled et al. 2013. Modeling trends from North American Breeding Bird Survey data : A spatially explicit approach PLoS 8. 4) Caswell. 2006. Matrix Population models.
5) Clutton-Brock et al. 2010. Individuals & pop: The role of long-term, individual-based studies of animals in eco & evo. TREE 25:562–573.
A final option is to be more conventional in the citation list and just remove citations and content from the proposal so that it all fits.

As a writer of (and occasional reviewer of) applications following this format - UK BBSRC grants - the most common approach I see is 'glob everything together', although personally I prefer to use short-format Science-style references. It comes down to personal preference really. It is so common to use the 'glob' approach that you won't be explicitly penalised for it by a reviewer, but as a reviewer I might subliminally be 'happier' reviewing the more legible version. Admittedly you can't fit as many references in but I can't remember ever having seen any application which I was inclined to mark down because too few references were provided.
(Disclaimer: this is based entirely on experience with BBSRC, other RCUK councils may differ...)


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When does a statistical consultant become a co-author or collaborator?
I am a graduate student in a small department and have become the go-to person for statistics advice among the other students.  I enjoy this but am wondering at what point I should expect, or request, becoming a collaborator on the project.  Pointing someone towards a method, a paper or a book is definitely not worthy of any recognition, neither would a short one-off 15 minute conversation in the hallway.  But what if I help them understand a difficult statistical method or fix some computer code that otherwise might have taken them days or even weeks to achieve on their own?  What if our conversations helps clarify the questions they are asking either statistically and scientifically.
I assume that if I became a co-author, I'd continue to contribute to the project, help write the statistical methods, comment on the full paper, etc.
I'm wondering if I should set up ground rules that I tell people, like, "the 1st 20 minutes are free, but after that, we'll have to talk about long-term collaboration."  Or I could come up with a list of services I can provide and what the expectations are.
This blog post comments on these issues from the perspective of a full-time statistician.  This StackExchange question addresses more general issues about co-authorship.

both your links go to the same blog post

This is a really good question.  Statisticians do seem to have a rather unique role in scientific research. +1 and I will look forward to seeing the answers.

There's certainly not a standard: I've list as a coauthor on a study for which I performed about one hour of analysis on, and was merely acknowledged (rather than listed as a coauthor) for another study where I provided close to 200 hours of consulting/work. One of these situations I found humorous, one I did not.

Since this thread just got bumped, I went and posted it to the American Statistical Association's mailing list. If you can login to amstat.org, you can read my message here. I did believe the ASA might have some guidelines on this topic, but couldn't find anything. If something useful comes out of the discussion and is not posted here, I'll update my answer, or possibly post a new one if the POV is different enough.

It depends who asks the questions from you: if only students, generally they have no influence nor incentive to tell their boss that you helped them, therefore you should be considered as a collaborator.

I went and asked this question on the American Statistical Association's mailing list. If you have a login to the ASA's website, you can view the thread here. I'll paste the answers in here without names (and cleaning up a bit):

Unless the consulting was very minor (in 10 minutes), the statistical consultant should in my opinion be one of the coauthors. It is a matter of ethics and not a issue of being paid as a consultant.  When I do the modeling and the analysis and the interpretation, I expect to be co-author. Sometimes I am the lead author. It seems to be a fight with the claim that "it is your job to do the consulting". I simply refuse such attitudes from faculty or clients.  The way I see it is that without our services, there would not exist a paper anyways.  Therefore, we must be co-authors.

I usually leave that decision up to the research leader and have fared well over the years. But then again, I consult in the area of agriculture, food, and natural resources, where the competition for attention is not quite as cut throat.
Personally, my benchmark is based on the answer to the question ' would this publication have seen the light of day without my involvement'? If the answer is no, then I should be a coauthor. If the answer is maybe or yes, then co-authorship is not really warranted.
An example, recently I spent quite a bit of time helping an author revise a manuscript that had been rejected, only to have the 'statistical expert' of the journal assume the 'my way or the highway' attitude. I suggested that the author not fight the 'expert' and get the manuscript published. The author had included me as a coauthor but I asked that my name be removed because of my personal criterion.

I generally agree with everyone so far but would like to add two little bits, that are apropos of co-authoring in general.
The initial question is very easy to answer — if you made a contribution you should be included as a co-author.
The next question is where on the author list should your name appear.
  When I was young I thought it should be based on the size of the contribution — I once argued with a colleague about who should be first.
  He felt that he should be since he provided the data.
  I claimed that the artistry was mine, and had he ever seen a painting signed Sherman Williams & Pablo Picasso?
  He prevailed.
As I got older I used a more Marxian approach - from each according to their ability, to each according to their need.
  What this meant was that I tended to put student or more junior authors first and put myself at the end.
  I have never regretted this choice.

There is, I think, no algorithmic answer to this question. The general principle is clear enough, anyone who has made an important intellectual contribution to the work should be listed as co-author. Ghost authorship is, in principle, as problematic as honorary authorship. The listed authors get artificially high credit if there are ghost authors. But then, one also has a duty to take part in the whole process with the manuscript. What constitutes an important intellectual contribution depends on context, the same contribution may be sufficient in a short article and too small in a larger and more complex work, usually the first author and/or the project supervisor should make that judgement.
There are also cases where an author has made an important contribution, but cannot agree with the conclusion and/or important methodological decisions. Then one cannot be listed as author. For instance, I have on some occasions made it clear that I could not be listed as author if the article included procedures such as stepwise regression, last observation carried forward or repeated measures anova.

Very interesting thread!  I proposed a roundtable lunch on this topic for JSM Vancouver but it didn't enroll enough to take place.  I'm glad to know that I was not wrong that there was some interest!
My own idea, which I got from several sources is:

I'm happy to meet for an hour with any colleague who has a stat question, just to be a good colleague and as a community service.
If we meet a second time, I would like some acknowledgment ... a mention in a footnote, or a note to the Dean, or some other professional marker.
Before we meet a third time, I ask that to continue I would like to be a co-author because it's rarely exactly three times ... the count seems to go once, twice, many times.  I am also then willing to work on the project in ways other than just meetings with the primary authors.

If I barely know the client and have to assume that his understanding of the non-statistical subject matter is correct, I often prefer an acknowledgement to co-authorship.  The same applies if I am presented with an experiment that was already run and don't want people to blame the design of the experiment on me.

There was also a recommendation of Parker & Berman, "Criteria for authorship for statisticians in medical papers", Statistics in Medicine, 1998, 17, 2289-2299, which I don't have access to at the moment.
In addition, many societies and professional bodies have general guidelines or criteria for authorship, although these may not discuss the role of statisticians explicitly. For instance, those of the International Committee of Medical Journal Editors were recommended twice (and do not discuss statisticians).

EDIT 2018-08-08: there were no more new replies to that ASA mailing list thread.

As an FYI, the ASA Thread is only available to members.

This is not an easy question, as are many other questions about coauthorship. To an extent, all answers will be opinion-based.
I am in a similar position. I work in industry but advise many of my wife's clinical & biological psychology students on statistical matters.
My personal cutoff point is somewhat later than yours seems to be. I'll happily invest three or four hours to help students clean up and understand their data, do some exploratory data analysis and plots and some simple models and release them into the wild with an initial R script. If that is the full extent of my engagement, I would be uncomfortable with coauthorship (but an acknowledgement would be appropriate).
Often, things go further than this. After this initial session, I'll code up more complex analyses, more sophisticated graphics, maybe research special models or approaches and/or read up on stuff. This usually involves some work on my own, multiple email exchanges and more personal meetings. At this point, we usually agree that I get coauthorship, and as you write, this means that I'll be a lot more involved in the rest of the manuscript's lifecycle.
I'll usually not write up the statistical methods section as you appear to do. My take is that the first author should have full ownership of the manuscript and should essentially understand everything in sufficient depth to describe even the statistics himself. After all, he will be the one to present it at conferences and/or thesis defenses. (It helps that psychologists get a lot of statistical training.) Of course, I'll go over and correct the methods sections, and I happily rarely find that the student fundamentally misunderstood the statistics.
If things have progressed far enough for me to be a coauthor, I'll usually be quite involved with the rest of the manuscript, too. I am rather anal-retentive and will happily nitpick the entire structure of the paper, the internal logic, grammer and punctuation. I don't know whether nitpickery is more generally a specific skill of statisticians, though... Of course, in maybe half of all submissions, reviewers ask about the statistics, and I often have to revisit the statistical analysis and/or at least its description.

Coauthorships arrived at in this way are actually pretty low-effort for me. Other people on the author list have spent weeks interviewing people in African refugee camps, juggling noxious chemicals in a lab and/or digging through prior publications. I, on the other hand, spend maybe one full work week altogether (sometimes more), sitting in a comfortable chair at my computer with a cup of coffee within reach. It's comparisons like these, and I'd guess that most statistical engagements are similar, that make me uncomfortable starting to discuss coauthorship after only one hour.

Laying down ground rules early on, as you suggest, is an excellent idea. Part of these should be how much time you can afford before thinking about coauthorship, whether this is 20 minutes or four hours.
One other thing, which the blog post you link to discusses, is that you as the statistician will need to understand the scientific context, so the researcher will have to spend some time explaining the situation to you. This time will need to come out of the initial "budget", since time does not grow on trees. Your client will usually try to handwave this away and insist that he only has "a little statistical question". This will usually not make much sense. If a client insists, you can always point him to CrossValidated for his "little question". If he gets a good answer there, great.

Every time I try to ask a "little statistical question," it always turns out that I'm asking the wrong question.

Thanks for the thorough response.  WRT "effort" invested relative to other authors,  me seeking to be a member of the team working on a paper will undoubtedly seem audacious to many.  However, I can get stuff done faster than my peers, either by doing it myself or helping them learn how to do it.  For example, I spent an afternoon helping a friend clean data using R which he would've probably spent a month understanding & manipulating in Excel.  Some might think I only spent a couple hours on the project, but I see it in terms of what I got done, not how long it took.

you have spent >10 years learning how to do it within a week. This contribution should not be underestimated

@user2173836: Someone takes their broken down car to the shop to be repaired. Mechanic opens the hood, looks in, gives the engine one THUMP! with his hammer, and closes the hood. The car runs again, good as new. Mechanic writes a bill for 500$. Customer is incensed. "500 bucks for one thump??" Mechanic takes the bill back, itemizes: one thump - $10. Knowing where - 490$.

I've recently dealt with this, and agree that this is largely subjective. Your proposal, to implement clear rules at the start, is highly recommended. I tend to do an "initial consultation" for free: an hour where we just sit and have coffee. If I'm interested, and have time, I'll suggest that I'd love to participate, but have to make sure that participation is respectful to myself and my other responsibilities. For example (as a professor), I'll fall back on something like "I'd love to contribute, but I need to justify the time expenditure to my department chair/dean/tenure committee/spouse/dog. Would you be comfortable treating my help as a collaboration that leads to authorship?" I tend to expound on a "minimum" contribution needed for that, write an e-mail summing up our conversation, and go from there.
One other thing to consider in these conversations are standards of ethics put forth by different professional organizations. I often work with psychologists, so I tend to lean on the APA standards (which I'll base the rest of my response on). A quote from the main page:

Authorship credit should reflect the individual's contribution to the study. An author is considered anyone involved with initial research design, data collection and analysis, manuscript drafting, and final approval.

On the website, this is directly contrasted with: funding, mentorship, and not participating in the actual publication. The last one is tricky, and how I interpret it is: if you aren't using analysis that I ran/interpreted, my statistical tables, any graphics I made, or any of my writing (obviously), then I'm not contributing. From my perspective, though, if you use even one of those things in the manuscript/presentation, I have contributed to the manuscript in a tangible way, and should be included. I feel obligated to mention (as this has happened) that, from my perspective, if you take my code and change the color of the plot and include it, you're still presenting a product of someone else (and need to provide credit for that).
I believe the need to provide credit is the primary consideration. If you have a published software, you shouldn't be given authorship as credit for its use (as a citation to the software is sufficient). If you have a paper on a unique method, you shouldn't be given authorship as credit for its use. Now, if you designed a program or statistic, you probably should be given authorship, as there isn't another appropriate way to provide credit (an acknowledgement doesn't count for that, in my opinion).
Speaking of that, I believe acknowledgements should come in for a small contribution that doesn't result in authorship (maybe data cleaning, data collection, etc). Notice that these have no writing and no tangibles of this will be used directly in the manuscript. If someone does something "monotonous" and writes, though (say, a lit review), they should absolutely be included as an author.
All said and done, having the conversation up front should indicate the type of compensation you get (and if you don't feel comfortable building a custom database from scratch for an acknowledgement, it is better to know that up front). Establishing a minimum, tangible contribution for that compensation establishes clarity for all researchers.

I'm struggling with this dilemma now.  The thing is, yes, we do need a stats person to properly analyze our data.  But we are paying a fee for the service and drawing our own conclusions and discussion from the crunched numbers.  I understand the position that their service is required for analysis, but at the same time I am paying them for a service, the same as I pay for a core facility to run an ELISPOT plate through a machine that spits out numbers.  No one would list the ELISPOT machine as an author even though the publication wouldn't be possible without it spitting out its numbers.  In the end neither the stats person nor the machine contributed to the design of the experiment or the conclusions drawn from the numbers that they gave us AND they were paid for their number crunching time.  On the other hand, had the stats person agreed to a collaboration where they were participating in the discussions of the meaning of the data and not charging me a timed fee for running our data through their software, then that is an easier definite "yes" they should be an author.

I would argue that if you're viewing your statistician as a number crunching machine rather than a person you're collaborating with (regardless of money), you need to revaluate your collaborative mentality.

But if they never actually speak to me or my student, how can that be a collaboration?

Why do you not speak with them before you conduct your study? Ronald Fisher has a famous quote To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of. If your number cruncher won't talk with you, find someone else to work with for future projects.

When the study began, we were capable of doing the power analysis and standard stats ourselves.  As we began to process the data, we realized there was more to the data that we had acquired than we anticipated. We then sought to confirm our original analysis.  Unfortunately our university does not have a fantastic statistician, so we set up a fee for service to confirm our data as I stated.  You are correct, for the future, I would prefer to set up at collaboration with someone that can contribute to the design and analysis. I just feel the current situation does not qualify as such.

It seems that the financial aspect changes the dynamic from one of collaborating peers who would both be receiving authorship credit as the primary reward for investments in the work. Justice is the equitable distribution of benefits and burdens. It would not be an equitable distribution of benefits and burdens for a PI, who has invested years in a project and then pays someone to run an analysis that can be done in a day or two, to also share equitably in authorship credit. That seems to be an inequitable distribution of benefits and burdens to me. An acknowledgement is appropriate, and any significant unpaid contributors should certainly be included as authors; however, paid, short-term consultants should be mentioned in the acknowledgement as authorship would effectively be double-dipping on the benefits side of the equation.


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Can one give a conference talk on a topic already published in a journal?
Let's say I wrote a paper and got it accepted in a journal. Can I then give a talk on that paper at a conference? What are the relevant factors here?

Most CS conferences explicitly forbid submitting papers that are already published or even under consideration by a journal.

What about conferences that don't publish proceedings?

I don't know of any CS conferences that don't have proceedings.

This may depend on your field and its customs.  In mathematics, it's totally acceptable and happens constantly.
However, if the conference publishes proceedings (only a few math conferences do), you should not publish the same paper in the proceedings.  Some people use the proceedings paper to write a "survey article" intended to give the reader a broad view of their work and other related developments in the field, but they would usually not consider this to be an original research paper.
In other fields, where a conference talk is considered to be like a publication it its own right, this might not be acceptable.

Similarly, in the atmospheric sciences we do this all the time. Most talks I have attended are either summaries of work already published or work still in progress (not yet ready for publication).

As others have mentioned, this might depend on the field. In my field (linguistics), I would say it's very uncommon to give a talk at a conference about something you've already published (a possible exception being invited talks).
I wouldn't say it's frowned upon, though - it just doesn't happen. And it doesn't happen for good reasons:
What is the point of giving a talk on something you've already published? You can't use comments and suggestions from the audience to improve your work, and why would the audience even listen to your talk when they can read your paper in a journal?
Maybe people in other fields think differently about these things.

It will depend very much on your field, and even the conference.
As JeffE mentioned, some CS conferences will expressly forbid papers that are already published, because the conference is meant to disseminate new work.
Similarly, some major medical conferences will have an embargo on the work until it is presented - this is often coordinated with the journal the work is being published in so that they go "live" the same day.
On the other hand, many conferences in public health have presentations expressly about previously published research, or on a study or topic for which multiple papers have been published.

I am from the Humanities (History), and I have increasingly heard that one should give talks only from published papers. I did not know that invited talks could emanate from published papers.


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Is it possible to survive in university academia without applying for grants?
I see that many professors spend all of their time applying for grants, minus a little bit of time to interact with the graduate students on their grants and a little bit of time to fulfill their teaching obligations. They are of course doing a great service to their graduate students, who perhaps otherwise would not be able to do research, but it doesn't seem very enjoyable to be in such a position.
I've spoken with many researchers at national laboratories who say they chose to go that route so that they could be mostly freed from the grant game (of course some of them still have to write grant proposals).
I enjoy doing research, but my real passion is in teaching, so my goal has always been to be a university professor. However, I am not fond of the idea of "hustling for money" (as one researcher at a national lab put it). I personally would much rather spend most of my time preparing strong lectures. (I would consider high school but the topics I would like to teach only are offered in universities.)
So, my question: can one survive in university academia without grants, perhaps at the cost of not having graduate students? Is it enough to be an effective teacher, with a strong albeit grantless research portfolio?

This depends heavily on your field - how expensive is your research?

Where I teach, there is a workload model (not academic rank) called "teaching intensive."  One chooses the teaching intensive model with consent of chair and dean.  Teaching intensive faculty are expected to teach four courses/semester, spend 15% of time on service, i.e. committee meetings, and 5% on research, which need not be funded.  So, it is possible, but one has to find the right place.

Oh, very good question. There are no real costs associated with my research (which is generally in the field of statistical/scientific computing): all I need is a computer, pencil and paper, and coffee. I have collaborated with several researchers who run very expensive experiments (people who give me their data to analyze), so perhaps that is why I have been exposed so heavily to the grant game.

What do you mean by "university academia"?  Do you specifically mean research universities?  There are a lot of teaching-focused universities, liberal arts colleges, etc., where teaching is a higher priority than research and funding expectations are correspondingly lower.  Jobs at such places outnumber those at major research universities, so this is the typical career path in academia.

@AnonymousMathematician I do not specifically mean research universities - I really mean any college where I could teach the courses that I'm interested in teaching. Your information is very reassuring, but it is somewhat at odds with my personal experience. I went to a teaching-focused state university for my undergraduate degrees (not highly ranked, in fact, you've probably never heard of it). But my thesis advisor there had 4 active NSF grants and was constantly pressured to obtain more. Further, he often remarked to me on how difficult and competitive it was to get even that position.

According to Wikipedia, there are about three thousand four-year colleges/universities in the U.S. (not counting nearly two thousand two-year colleges), and the NSF awards about ten thousand grants per year.  NSF grants are typically for three years, so the average number of active grants per institution is about ten.  (And I'd guess that at most places it is substantially lower than that, since research universities hold a disproportionate share.)  So four active grants for one PI would constitute outstanding success at fundraising in most institutions.

One issue is that there's a sizeable group of universities that have not been especially research-focused in the past but would like to change that.  There, one might run into pressures one would not expect given the university's history.  (This can also vary at the departmental level.)  But I believe this is still only a small fraction of academia.

@BobBrown Would you please turn this into an answer so that I can vote it up?

@jakebeal:  Thanks for the thought.  I think Brian's already covered it thoroughly, though.

Grant money includes a significant chunk of "overhead" or administrative costs that help to support a department and the university in general.

There are certainly some situations in the US where you can be a tenured professor, do some unsupported research, and never bring in grants.  However, the expectation that you will bring in research grants is fairly wide spread, and having at least some grant funding is necessary to obtain tenure at a surprisingly large number of institutions (not just the "Research I" nationally ranked universities.)
Research funding varies dramatically between disciplines.  In the following I'll restrict my attention to mathematics since you mentioned that was your area.  I'm including statistics since in many cases statisticians get jobs in mathematics departments at these kinds of institutions.
The exceptions boil down to universities in which research is not a high priority and teaching is more important.  These institutions are typically "Regional Comprehensive Universities" often with names of the form "directional state university."  For example, in New Mexico we have "Eastern New Mexico University", "Western New Mexico University", "New Mexico Highlands University", and "Northern New Mexico College"
Teaching loads at such institutions are typically high (3-3 or 4-4, plus lots of advising) and graduate programs are small or non-existent.  Undergraduate
science and engineering degree programs are also small.  Many of these universities don't offer any degrees in engineering.  Much of the enrollment in math and statistics courses is in freshman level service courses like college algebra and intro to statistics.
In order to get hired into a tenure track position at such an institution you'll need a PhD and some teaching experience (many candidates for such positions will have worked in "visiting assistant professor" positions for a few years.)  There will typically be some expectation that you will publish research during your time as an assistant professor, and you may be encouraged to apply for research grants, but very few faculty at such institutions actually have grant funding from the NSF or other federal agencies.
In mathematics, the number of tenure track positions has been in decline in recent years.  The competition for these kinds of positions has become extreme, with institutions reporting hundreds of applications for each position.

As a comment on your last sentence, readers should note this doesn't necessarily imply that supply of job candidates is outpacing demand by a factor of hundreds.  In the last several years, math departments in the US have largely adopted http://mathjobs.org, a central employment clearinghouse, and as a result it is pretty easy for each candidate to submit dozens or even hundreds of applications.  So the total number of applications has increased dramatically, but the change in number of candidates and/or positions may not be so dramatic.

(I know you know this, but other readers may not.)

Nate's absolutely correct.  However, looking over the 150+ applicants for a tenure track position at my institution, I see many well qualified applicants who've spent years in VAP positions without landing a tenure track position.  It's pretty rough out there.

You say in your comment that "[t]here are no real costs associated with my research," which is a huge misunderstanding about the costs of research. The vast majority of research budgets (in the US, based on my experience) are salaries for the researchers. While NSF limits professors to 2 months of salary across all grants from NSF without special permission, many graduate students and postdocs are funded mostly or entirely off grants won by those professors. If you want to have a grad student work with you on your research, you need to fund their salary and tuition, as well as their fringe benefits and the university's overhead charge (which keeps the lights on and pays for admin staff, etc), and at most universities this money comes from external funding. I guess that students who TA can also do unfunded research with a professor as they work towards their PhD, but this seems unfair to them unless the other requirements (classes, quals, etc) from their department are minimal.
Most universities in the US cover 9 months of salary for professors, so if you want to be paid that other 25%, you need to bring in external funds or teach classes during the summer semester/quarter.
How much of this you choose to do will depend on how ambitious you are. If you want tenure and raises, you will almost certainly be required to win some grants. Though, once you have tenure, you can basically stop winning grants and support no students, though your colleagues will probably stop giving you raises at that point as well.

Another point worth mentioning is that grants are very helpful for funding travel to conferences for you and your graduate students.    Institutional funding for such travel is often non-existent.

True, though in comparison to salaries, this is not typically a large portion of what a grant funds.

Yes, but in the other direction, if you don't have grant funding, then the lack of travel funds can be the singlest biggest thing that stops you from doing research (particularly assuming that your graduate students are working as TA's.)

@BrianBorchers, I find that surprising. There's still so much research that can be done without presenting at conferences.

I'm just saying that networking is really tough for faculty who don't have grant money and don't have institutional support to travel to meetings.  Time (at least summers and breaks between semesters) is reasonably available even to someone teaching a high (3-3 or 4-4 load)  Many mathematicians need little more than a desktop computer to do their research so equipment isn't much of an issue either.

@BrianBorchers, I agree that networking is hard without travel, but that's no reason to stop working!

I think we agree on that.

In many US institutions, including R1, there are professors whose primary role is teaching (plus some services, but no research). These are called Lecturers or Teaching Professors, depending on the institution. Another possibility is teaching at a community college.


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Inquiry for Ph.D admissions in European countries
I want to pursue a Ph.D in Chemistry and the destinations of my choice are Germany, Switzerland, Netherlands and Sweden. Can anyone please tell me the scholarships and fellowships available to which an Indian student can apply in these countries? (I know of a DAAD fellowship for Germany)
I would also love to know if there is any centralized admission process to these countries (similar to US)?
Thank you

The answers in the following thread should answer most of your questions: http://academia.stackexchange.com/questions/24474/phd-in-europe-without-scholarship-from-non-european-homeland

There is no centralised admission in the US for PhDs.

@Greg: "Centralized" in the sense that you apply to departments rather than advertisements for individual PhD positions.

PhD students in the Netherlands are usually employed by the university (these are AIO, or "assistent in opleiding", positions). As far as I know, anyone can apply for these jobs and it doesn't matter where you're from.
You apply directly to the faculty that is advertising the position, and after you are chosen for the position the university sponsors you through the visa process as a "knowledge migrant".

There are also occasional grants offered by a body called NWO. The PhD grant is called Top talent, but it isn't always offered.