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Is it safe to post one's research on web sites like Math Overflow for "peer review" before submitting to a journal?
Suppose in mathematics, someone finds a completely new elementary proof of a famous theorem and wants his work ''peer reviewed'' on a site like MathOverflow or MathStackExchange before submitting to a formal journal. How safe would this be ?

Mathoverflow and Math.SE are not for peer review. Your post will be closed very quickly.

"someone finds a completely new elementary proof of a famous theorem and wants his work ''peer reviewed'' on a site like MathOverflow or MathStackExchange" -- then they are probably not experts (or else they would know to publish in a journal), hence their proof is most likely wrong.

@FedericoPoloni but even when it's closed, the post notice will contain helpful links to show how should one can improve the post?

@Ooker There is little hope to 'improve' a post on a subject that is completely off-topic.

If you post under your real name, I think that it is quite "safe" in the sense that your work is unlikely to get stolen because of this.  In fact, posting your work on a public forum is the best defense I know against intellectual theft.
On the other hand, "Is this proof of a known result correct?" is generally not regarded as an appropriate MathOverflow question.  There can be a fine line between asking questions that come up in one's research and asking others to vet your research.  The former is the purpose of the site, whereas the latter is discouraged.  Your question seems to fall on the wrong side.  I think it would stay open, at least, on math.stackexchange.com.
If you have not already published work in the past, I might recommend that you try to get one-on-one help from a qualified (and trusted) mentor, rather than trying to crowd-vet your proof.  It is not impossible to do research mathematics completely independently and with no academic affiliation -- I have seen people do so quite well -- but it is very rare and much harder than doing it with some assistance.  It would be reasonable to seek help from the math department of any university near you.  If the mathematicians you get in contact with can't help you, see if they can connect you to someone who can.
Postscript: I have observed on this site and others that amateur mathematicians often have significant concerns that their work will be stolen.  I think these sentiments are very unfortunate, because they can serve to prevent these people from getting what would benefit them most: qualified help and supervision.  I don't want to say that it is strictly impossible for someone's work to get stolen, but here are two things: (i) I have done mathematics for my entire adult life (more than 20 years), and I have never seen or heard of an amateur mathematician's work being stolen by a professional mathematician.  Reports of theft of mathematical work of anyone by anyone have come to me...but very, very rarely.  (ii) I would estimate that about 90% of the work done by amateur mathematicians is not publishable.  This is not to say that most amateur mathematicians are hopeless or incapable of doing real, publishable work.  However most professional mathematicians train for years and make use of enormous amounts of human capital in order to get to the point where they can do and write up publishable work.  If they had been afraid of showing their work to their mentors, they would not have gotten anywhere in most cases.  Just something to think about.

If you are an 'outsider' to the mathematical community and you have an argument which you believe provides a significant mathematical advance, you may well have broken new ground - but you should also seriously consider the possibility that your argument contains a mistake, and you should carefully think about your interactions with the mathematical community in that light.
I don't say this to discourage you, but I do want to impress upon you that you are part of a relatively large community of people who will look much like you to a mathematician - see for example the questions Handling unsolicited proofs of famous mathematical problems and I believe I have solved a famous open problem. How do I convince people in the field that I am not a crank? on this site, which give a good impression of the volume of similar requests your work is likely to be embedded in. Again, this is not to discourage you, but to encourage you to think carefully, and take your time over, how you engage with professional mathematicians you are asking to review your work. If nothing else, make sure you read and mull over all the answers on both threads.
That said, when you do communicate your findings to outsiders, you are justified in seeking protection for your work so it isn't later claimed by someone else as their own. I would generally advise you to take it easy on such protections: your main problem is overwhelmingly more likely to be getting mathematicians to take your manuscript seriously, not defending it from theft.
In that regard, the best defence I can think of is to make it publicly available, as widely as possible, under your real name. This can include posting your manuscript to the arXiv if you can post there, to viXra as an alternative, or to sites like MathOverflow or Math Stack Exchange. For good measure, if you post on Stack Exchange, you might want to ensure that your post is archived on the Wayback Machine. It's important to note that even then, your work is not "safe" in that someone else could, in principle, take that work and submit it as their own to a journal.
However, this is academic misconduct of pretty much the highest order, and if that were to happen you should contact the journal editor and the dean of the author's institution with proof (like your MathOverflow post!) that you are the original author of the unattributed work. That is immediate grounds for an investigation which can result in retraction of the paper and severe academic sanctions against that author. If it ever comes to that.
It is also important to note that, regardless of whether your work is safe or not, it may or may not be appropriate to make such a request of MO or MSE. In particular, the threads Using Math Overflow to check whether or not a proof is correct, On discussion of published papers at MO, and Appropriate or not: “To what extent are the results in Paper X correct?” indicate that such a request would be considered off-topic at MathOverflow. To tie this in with my initial point, posting review requests in inappropriate venues is a good way to quickly exhaust the goodwill of the mathematical community and make it much harder for your work to receive appropriate vetting even if it deserves it.
So what should you do? I would start with this advice.

This is a very good answer (and similar to mine, which I wrote rather slowly).  I want to point out one thing: "It's important to note that even then, your work is not "safe" in that someone else could, in principle, take that work and submit it as their own to a journal." You're not wrong, but I think it's even more important to note that all mathematical work is not "safe" in this sense.  Already published work, including of establishing and famous mathematicians, can also be improperly appropriated and published in this way...and in fact I think that kind of theft is more common.

I would actually advice against uploading to viXra. To many, that would be a signal that the author did not want to do the minimal amount of work required to be able to upload to arXiv instead (even if this is not true).

@TobiasKildetoft That is true - a manuscript in viXra is definitely a strong signal that many will take negatively. However, it is easy to forget from within an academic institution that not everyone can post to the arXiv, and that the 'minimal work' of finding endorsers is precisely what we're advising the OP to do carefully. As regards the question, the OP would be justifiably worried that, if they send a manuscript to an arXiv endorser, that person could 'steal' the work. A viXra submission - even if suitably undisclosed to such a potential endorser - is a powerful insurance policy.

I disagree strongly that the OP would be justified in their worry, as long as they actually put some thought into their choice of person to contact. The worry might seem justified by someone from the outside, but that does not make it so.

@TobiasKildetoft I agree that it is highly unlikely that a potential endorser would steal work sent for such purposes. However, you cannot fault an outsider for considering that unsafe (even if it probably isn't). In any case, saying that posting on the arXiv requires minimal work is disingenuous at best.

Compared to actually writing a paper worth putting on arXiv, it really is minimal (it might take some time, but that does not increase the amount of work).

@TobiasKildetoft Apologies, but that really is disingenuous, and it is based on the fact that someone with an academic email address can simply go and post; without one, you can't. Instead, you need to find and convince suitable endorsers that your manuscript is arXiv-ready, which means you need to get endorsers to read it and you need them to respond to your emails to begin with, which means that you need to tackle all the challenges of getting taken seriously. Calling this minimal is like laughing from atop the ivory tower.

Sending an email with the paper and a request for endrsement takes a few minutes. The waiting time until getting (or not getting) an answer is not work, it is time that can be spend doing other stuff.

@TobiasKildetoft I'm not sure at all that encouraging such people to take that step lightly is at all helpful. (I wonder, for example, if you'd advise people as nonchalantly to send unsolicited email if you yourself received a significant volume of such emails on a regular basis.) Pressing 'send' is easy; it's getting the email right that we should be advising people to do carefully (which Kaveh and Pete Clark have done well). Simply put: I disagree with you. But we should probably leave it at that.

If you say you have found a completely new elementary proof of a famous theorem, you instantly put yourself into the 'nutcase' box until you can prove otherwise (or unless you have already proved otherwise). Posting on MathOverflow is a good step to additonally move into the 'nuisance' box as well. Even if you are right, you have not attached your name to the proof in any formal way, so someone could steal it. Probably the route that is most likely to win you acceptance within the mathematical community is to find someone at a university or similar who is willing to mentor you, and don't conclude your proof is correct until you can actually convince another mathematician it is correct. If it really is elementary then that shouldn't prove so difficult.

"If you say you have found a completely new elementary proof of a famous theorem, you instantly put yourself into the 'nutcase' box until you can prove otherwise" That seems harsh to me.  E.g. 'There are infinitely many prime numbers 'is a (very) famous theorem, and completely new elementary proofs are often found.  "Even if you are right, you have not attached your name to the proof in any formal way, so someone could steal it." I really don't agree with that: if you post the question under your real name, then you are identified as the author.  I don't see what formality has to do with it.

@PeteL.Clark Ok, yes, you're right. I took the question to mean an elementary proof of a result that doesn't currently have one. The question does suggest the intention is to publish in a journal, which would not be a realistic option if many elementary proofs exist. Posting under your real name would attach your name to it, but there's no system to guarantee who chose the name. It might sound silly to wrongly give credit to someone else for a right result, but could you similarly post poor-quality work using someone's name?

The line "don't conclude your proof is correct until you can actually convince another mathematician it is correct. If it really is elementary then that shouldn't prove so difficult." is pure gold.

@PeteL.Clark So you're saying I can steal someone's idea, post it on Stack Exchange under my real name, and I'm identified as the author? I don't think so. Being the first person to post it in an online forum proves nothing - at best it is evidence that can lend weight to an argument which is supported by other evidence.

"Posting under your real name would attach your name to it, but there's no system to guarantee who chose the name." I'm not sure I completely understood this.  There's no system to guarantee that the names appearing in most published papers are not completely made up (and every once in a while, they are); institutional affiliations are not always required and rarely vetted.  Anyway, if the identity cannot be verified, then the post itself would be cited by any mathematician using the work.  I find the idea that people can steal your ideas if you don't present them "formally" quite bizarre.

@JessicaB: "The question does suggest the intention is to publish in a journal, which would not be a realistic option if many elementary proofs exist." A colleague and I are running a graduate seminar on the process of mathematical research. We began with the theorem that there are infinitely many primes, and at one stage asked the students to find all papers in the last five years that give new proofs and/or generalizations of this result. We got about 50 papers. New, elementary proofs of famous theorems are published very often: not in Inventiones, but in other journals

@JBentley: "So you're saying I can steal someone's idea, post it on Stack Exchange under my real name, and I'm identified as the author?" No.  "I don't think so." OK, good.  In case it is necessary, let me say that you should not try to steal someone else's mathematical idea.  This will likely work out badly for you: it could be the end of your mathematical career.  By the way, I have several times used postings of mine and others math.SE and mathoverflow.net in my later published papers.  I have never had any problems.  If you have different experiences, please let me know.

@PeteL.Clark Seriously? Clearly I picked the wrong topic. But I'd be curious to know for how many of those papers the proof you're refering to is the main focus of the paper.

@PeteL.Clark I think you missed my point. I'm not suggesting that I'm considering stealing anyone's idea. I also don't dispute that you might be able to post your ideas and have no issues result from it (i.e. my point is not about whether you increase you risk of theft). I was responding to your assertion that, "if you post the question under your real name, then you are identified as the author". That is not the case, because a thief has just as much ability to post material under his real name, as the real author. The mere act of posting it proves nothing by itself.

@JBentley But the time stamps on different posting or dates of publication would serve as evidence to figure out who had the idea first. If person A posts their new proof on mathoverflow, and then person B takes it and sends it to a journal, person A could be able to claim priority for it. I don't know if such a controversy has ever happened in real life.

@JBentley: By the author, I meant the author of the post.  This is a response to an answer claiming that one must communicate one's ideas in a certain "formal" way in order to get credit for them.  My response is: no, as long as you see that Person X said Y, if you use it in your work, you must mention that X said Y; there are no further bells and whistles involved.  If Y is plagiarized from person Z, then this identification is problematic, but I am not talking about that.  Anyway, in what context have you ever had to prove that you are the author of a mathematical document?

@user90219 how do you figure that the timestamp proves who had the idea first? All it proves is who posted it first. By your reasoning, B could steal someone's idea, post it to get a timestamp, and then "prove" that he had the idea first.

@Pete ok, I see your point now.


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Order of authors when publishing bachelor's thesis (CompSci)
Forgive me if this is a duplicate; i found a few somewhat similar questions, but none which matches my situation exactly.
I wrote a bachelor's thesis in computer science. After I was done, we (myself, my supervisor, my professor) tried to get it published. We have succeeded now after some unsuccessful attempts and a few days ago, my supervisor asked me whether I would be okay with him being the first author on the paper, which would help him towards completing his PhD.

Would I be correct in refusing this? I just don't see how I can NOT be the first author when it is my own thesis. Note that naturally, we did not publish the exact thesis; we significantly shortened it. It is a review paper and the bulk of the review work is still my work; he added main parts of the conclusion and some things throughout the paper
If I am correct in refusing this, how can I communicate this? Is there any document which might help me in formulating an answer? So far, I have only found a document by the APA which says "A student is usually listed as principal author on any multiple-authored article that is based primarily on the student’s dissertation or thesis." [1] Does anyone know of a similar document for computer science / the natural sciences? AFAIK, my university doesn't have an explicit rule; it only says that the authorship of a thesis is solely with the student since anything else (e.g. having the advisor as co-author) would be against the notion of a thesis being a demonstration of the student's capabilities.

TLDR:

publish modified bachelor's thesis
get accepted
Supervisor: Can I be first author?
Want to say no but not sure if I'm right / how to communicate

[1] https://www.apa.org/science/leadership/students/authorship-paper.pdf
Edit
The subfield is rather applied.

Where is this, please?

I'm inclined to agree with @Buffy's suggestion that the location is likely to be important here. It strikes me as very strange that being first author on a review paper co-authored with an undergraduate would help your supervisor toward completing his Ph.D. But I realize that some places regard as completely standard things that strike me as very strange.

There is no "standard" for first author, second author or 24th author, it seems to vary proportionally to the number of institutions and supervisors... Perhaps you need to do what is "politically" correct or easier - you will have other publications during your career...

@AndreasBlass I can only imagine that for his PhD he has to publish X papers as first author ... But in that case, being the first author on a paper for which I did most (but not all) of the work would be rather questionable!?

Actually, the concept of "first author" is a bit foreign to CS in most places. Authors are listed alphabetically and only contributors are listed as authors. You say the supervisor contributed to the paper and if so should be an author.
I think you are correct to refuse if it is your thesis that is being published, and I think the university will back you on it. I hope so, anyway. But for a paper "related" to the work, it is a different issue.
But, you have a political problem. One way to handle it is not to publish a shortened version of the thesis jointly, but an extension. Publish the thesis under your own name, but acknowledge your advisor. Then get to work on an extension.

The concept of "first author" is common in other fields, of course, but not really in CS or in math.

How authorship order is handled varies by CS subfield. As a general rule though, subfields closer to math tend to go with alphabetical order.

It seems like the PhD-student supervisor wouldn't have asked to be first author if they were in a CS subfield where first authorship didn't matter.

It's also not true in applied math, where first authorship often indicates the majority of work done.

I'm very happy with the fact that my supervisor is an author, my question really only addressed the first author issue. I mean, it kind of works both ways: If his argument is "Let me be first author since ordering doesn't matter", I can counter with "No, I want to be first because it doesn't matter anyway."

Regarding the "political problem": I actually don't think that I have a political problem because I've already left the university. Publishing the (slightly modified) thesis is an endeavor we all agreed upon, but there's no leverage or pressure involved ...

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Recalling standard results in a master's thesis appendix for reader's convenience and/or self-containedness
Currently working on my master's thesis, I know that I have to consider that I am writing for an appropriate audience, that is, I write for people who have at least a bachelor's degree in my field (mathematics).
However, I need to use standard results that one learns in third year (in my institution, at least). In particular, these results can be found in any "basic" textbook in the field my work is lying in.
I face a particular dilemma: either just citing the name of the theorem when I use it in the main work without giving any reference, or rewriting the theorem in the Appendix for the reader's convenience (with appropriate reference to a "basic" textbook).
Of course, my supervisors will know these results, but my peers may not remember them and a master's thesis is often expected to be self-contained. I don't expect many people to read my work, of course, but still, I want it to be as "perfect" as possible.
This question is related but it seems the OP is speaking about a basic theoretical concept they would briefly discuss in the main work. Precisely, it would not belong in the appendix, which makes the question different as I am not discussing these basic results: I just use them.
Question: is it acceptable to rewrite classical, basic results in the appendix section of a master's thesis and citing basic reference works about these results for the reader's convenience and/or for the work to be as self-contained as possible?
I shall of course ask this question to my advisor but I wanted to have different advices from professionals on this.

Related:  http://academia.stackexchange.com/questions/45946/should-i-include-independently-derived-but-not-novel-results-in-my-thesis/45947#45947

@Buzz Thank you, your answer on that question is really interesting.

If you're just going to repeat the statement of the theorem for the reader's convenience, then I would just include it in the text at the point where it is used.  I wouldn't send the reader to the appendix, unless the statement is exceptionally long (say a page).
If you decide you want to include a proof of the theorem, then I would put the proof in the appendix (and repeat the statement of the theorem there as well).  This is not too unusual in a master's thesis, if you feel it would be a good exercise for yourself to prove the theorem.  But it should be your proof; don't just copy a textbook proof verbatim.

Thank you for your answer. Including the theorem where it is used can be a better idea, indeed. I was/am afraid to recall results that could be considered as too basic to be reminded to the reader but I suppose I shouldn't.

My answer is very similar to the one I gave to the question I linked to in a comment:  There is usually no reason not to include something in a thesis.  Your thesis is a place for you to give a coherent account related to your work on a topic.  There are (usually) no page restrictions, and it should serve as a reference document for future readers.
Many theses include a lot of review material, beyond just what might be contained in a literature survey. A thesis has to contain new material, of course, but it does not all need to be novel, and there can be a lot of merit in giving detailed explanations of known results, if the readers are not necessarily going to be familiar with them in detail.

"There is usually no reason not to include something in a thesis": I somehow disagree here. What I usually tell to my students is that there is no reason to include something that it's written much better elsewhere. Either offer a different point of view, a better explanation, a more up-to-date review or just put an appropriate reference.

@Massimo Ortolano. True: I always tried to convince the students not to write a 30 page trivial introduction to the general subject. It does not add any value to the thesis and bores the supervisor.

You are looking for a decision between two alternatives - to cite you:

just citing the name of the theorem when I use it in the main work without giving any reference, or
rewriting the theorem in the Appendix for the reader's convenience (with appropriate reference to a "basic" textbook).

I'd go with alternative number 3:

give the theorem, along with a reference that allows the interested reader to follow up - that is, something like "(Foobar, 2016, Theorem 3.14)".

It makes sense to give this information, especially for propositions that non-experts may not know immediately. Conversely, I don't see the point of rewriting a theorem and its proof in an appendix. If you are too literal in copying, you are close to plagiarizing (unless you clarify that you are copying something verbatim - but then, why do this?), and if you reformulate, you run the risk of introducing errors of your own. Better to rely on standard textbooks.
Yes, a thesis should be self-contained, but of course it never is, and if you use a result from a standard textbook, then this should be easily available to any interested reader.
Of course, if you need to refer to more obscure material, possibly in a foreign language, or if you need to discuss the referenced result in some way, perhaps to point out an error in a proof, then it makes sense to devote more space to it. In an appendix, if the discussed material is not really germane to your main topic.

"copying something verbatim - but then, why do this" the reader of a PhD may not have access to paywalled content.

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Homework Policy - Extension with Partial Solutions for Partial Credit
I'm going to be teaching my first course in the fall semester, and I've been trying to think of ways to make the homework benefit the students. One thought I had was to have the homework be due the week following its assignment for full credit, at which point partial solutions would be posted to the course site, or at the following lecture for partial credit. I can think of variants where parts of the assignment could be submitted at each deadline, so if a student figures out how to do problems 1, 3, and 4 but has no idea on problem 2, he can submit the three he figured out for full credit at the first deadline, then use the partial solutions to figure out the last problem and turn it in for partial credit at the second deadline.
What are the benefits and drawbacks for the students and administrators of such a system? Students: Is this a system that you would find helpful? Instructors: Have you tried anything similar in the past, and if so, what were the results?
This is what I've been able to think of so far:

Administrators

(+) Encourages students to look at the solutions
(+) Helps homework be a learning experience
(-) Requires two sets of solutions if full solutions are posted later
(-) Requires more organization, especially if students are allowed to submit on multiple days

Students

(+) Provides an extra resource when working through the assignment
(+) Encourages completion of the assignment, which should increase retention because students are using (some) of the knowledge
(-) Confusing system
(-) Assignments will overlap if assigned weekly

Perhaps you could elaborate on how you plan to distribute partial solutions? For example, if student A has difficulty with problem 1, and student B has trouble with problem 3, how will you ensure that these two students don't just share their partial solutions with each other?

@Mad Jack Partial solutions would be posted online to the course site after the first deadline. Because the opportunity to turn in the assignment for full credit has passed at that point, it doesn't matter (from a grading perspective) who has access to which problems.

Got it. You could consider editing your post with the above clarification [or not, in case my misunderstanding is an outlier].

This system is also used in my university, but the deadlines are not so strict. We have 3 deadline across the semester, which is better than weekly deadlines in my opinion. Also, the students are encouraged to talk to each other in order to understand better the theory.

@MikeyMike Can you clarify how the deadlines across the semester are related to the system I've proposed? Of course the students would be encouraged to discuss; this would just be an additional tool.

We have three dates to come with the solutions for the homeworks. If I take the example of the second semester, we would have something like: 6 weeks to the first homework, another 6 for the second homework, and in the day of the exam we present the project. The final grade is in our case: 40% exam+20% first homework+20% second homework+30%project. Note the additional 10% over 100% as a bonus. Most of the students have passed with 70-80%. If the students present the solutions over the deadline, then it would not take the maximum.

I give weekly assignments and post the full solutions immediately after the assignment is due.  However, I also give partial credit (50%) to any assignments turned in after its due date but before the final exam.
I have seen a handful of students utilize this system.  Typically they are the ones who normally complete assignments but missed the deadline due to extraneous circumstances.  I consider these use-cases to be exactly in the spirit of my policy.  Occasionally, I will have a student who submits virtually all of the assignments in the last week of the term.  I see this as an unintended consequence of the policy (I would actually prefer to discourage this kind of procrastination).
There are a few downsides from an instructor's point of view:

There is a higher organizational load than if you enforce a strict deadline.  I find the marginal cost of grading a late assignment to be surprisingly high.  If assignments came any more frequently than weekly, I am confident my system would become onerous, and the one you propose would be even worse.
There is a risk that an honest (but poor) on-time effort by a student could be surpassed by a dishonest late effort by another student.  I haven't seen this but it is a worry in the back of my mind.  I try to avoid this by actively encouraging students who do poorly (worse than 50%) to re-submit after looking at the solutions.

Why do you think that the system I'm suggesting would be even worse from an organizational load perspective? The way I've conceived it, nine days (or thereabouts) after the assignment is released, the instructor can post full solutions and grade the assignment as normal, aside from needing to sort together two piles.

@Aliden that may have been my misreading of your idea (or more likely my projection of your system onto mine).  If the "partial credit window" is only a few days, I could see that being a manageable system.  Note, however, that every day you grant in the "partial credit window" is a day that I would see as a delay in getting the graded assignments back to the students.  (This last part might not necessarily be true, but it would be true knowing my tendencies.)

I think this is a really good idea. Students who have no clue how to solve a problem need to figure it out and work through it. If they can't do it initially by themselves, then your partial solution will help them, and they'll get partial credit in exchange.
I will add that judging by you saying it'd be "confusing", that assignments would "overlap", and that you'd need more "organisation" to handle the assignments .... it seems you expect many students to make use of this extra deadline? If so, I think that'd be nonoptimal. The vast majority of the students should deal with the vast majority of the problems as they normally would: working on them, following up on their ideas, solving it, and turning it in on the first deadline. You can ensure this by only giving a very low amount of partial credit if they happen to use the second deadline and your partial solution.
Your system should only be in place for that small subset of students working on a small subset of problems that they truly have no clue what to do with. It should be there to ensure that everyone works through and understands everything (and your partial credit is the reason they'll do this, so while it should be low, it should still be something they're gonna want). If the partial credit is too high, not only will all those weaknesses you mentioned come into effect (very confusing system because now students have to measure the probability of their initial solution being correct versus the partial credit they'll get if they wait till the second deadline, it'll require more organisation since many students will be using this system, and it'll give you many overlapping assignments, again because many students will use it for many problems), you also risk making it very unfair towards the students who worked it out for themselves.

Thank you for the answer. In my initial post, I was intentionally harsh because I think it's a good idea and I wanted to be clear about any shortcomings. I think that your comment about the amount of partial credit is spot on, and that becomes the way to adjust how many people will tend to use the system.

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Is possible cite an internet site (of an academical project) with the authors
I am writing a paper about a project.
I must cite the internet site of the project with the results.
Question: can I cite, not only the site, but also the authors in the references?
NOTE The site is of research team where I work and is an institutional site (linked to my university).

possible duplicate of Attributing contributions to academic work that occur in Stack Exchange

I think that might depend on a particular publication style that you use (APA, Chicago, etc.). I would advise to consult the corresponding section of the style guide for specific guidelines.

Yes, you should always provide all of the bibliographic information that you can.
In the citation of websites, authorship is often not given because authorship is either unstated, unclear, or complex.  If, however, the authorship of an online resource is clear, then you must list its authors, just as you would for any other source that you cite.

I'd add that a number of websites explicitly state how to cite them. It is thus better to firstly have a look for this kind of information.

@MassimoOrtolano: IMHO, the publication style guide should override the recommended citation by the website or its authors. Otherwise, the style of the publication will be inconsistent.

@AleksandrBlekh: the "how to cite" pages do not generally recommend a fixed citation style, but rather they can provide additional information (authors, title, release date, permanent link) not necessarily provided in the home page. This information can than be formatted in agreement with the publisher's preferred style.

@MassimoOrtolano: In my experience, many pages asked for a specific style, hence my comment. I'm glad that we agree on the main point, which is that publisher's preferred style should take precedence.

I would make it a WebCitation (http://www.webcitation.org/) so that your link continues to work even if the website you cited is later taken down.


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Is it good to buy health insurance for time period between the date of entry into US and the date on which university insurance coverage starts?
I will be soon joining a PhD program in US on an F-1 student visa. I will be entering US about 20 days before the university academic session starts. The university will be providing health insurance to me, and coverage will start with the academic session itself. So I will not be covered by university insurance for my first 20 days in US. I would like to know if it is a good idea to buy a short term health insurance policy for these first 20 days in US ? Is it very risky to not buy this short-term insurance ? FYI, I do not have any chronic diseases or other things.
Since US healthcare system is very different from everywhere I have been to (some European and Asian countries), I am in utter confusion regarding this whole health insurance stuff. Any answers would be really appreciated.
Thanks in advance.

Just checking back: you have an F1 visa and not a J1 visa, right? The answer to your question depends on this difference.

Yes, I will be entering US on an F-1 student visa. Thanks

How is your financial situation? Can you afford to buy the short term health issurance, say in a few hundred US$ range?

I will get stipend in the PhD program so my financial situation is not that bad. I will get my first paycheck as well when the academic sessions starts. But the thing is that I want to take the least amount of money from my parents as I do not want to burden them.  It is only a matter of first 20 days. I think if the insurance will cost me more than $100 then I do not think I will buy it. The whole admission process has been very costly anyway with all the exams, etc.

I wonder if this would be a better fit over at expats.se?

The question is definitely a better fit at expats.se, but the readers of this SE are more likely to be able to answer it.

Yes, it is worth it. But it is sufficient to restrict yourself to emergency coverage. The most likely scenario in which you will need a large sum of money during that time span is an accident, but a sudden illness is also likely. And an initial entry to a foreign country you are unfamiliar with is a high risk period. Try to have some local (at least within the US) contacts in case of an emergency, in any case.

Travel insurance is generally pretty cheap, especially if you exclude high risk activities like skiing and parasailing. My UK bank provides travel insurance for free and some credit cards provide travel insurance for free if you book your flights with them. If you were taking a three week vacation to the US, you should be able get insured for well under $100.
The issue is that you are not taking a vacation. You are entering the US on a F-1 student visa and possibly do not have a return ticket. While many travel insurance providers will happily sell you insurance and tell you you are covered, they will also direct you to pages and pages of terms and conditions. The key to insurance is making sure you meet all the terms and conditions, otherwise they will not pay out when you need them.
Assuming you can find reasonably priced insurance, the question becomes do you need it. Travel insurance generally only reimburses you for expenses and does not pay the bill up front. This means the benefits are often limited by how much you can afford to pay up front. There also things you can do to reduce the need to see a doctor (e.g., getting a round of general antibiotics from your doctor before you leave). Overall the answer is highly personal and depends on how you would pay a huge medical bill.

I thought since the OP is moving residence, and not traveling, that travel insurance does not apply. Hence 'repatriation' in the event of a major illness may not apply either. Check the fine print.

I would say yes. You can likely get fairly cheap insurance from your (or your parents') home insurance, or the credit card company that you bought your ticket from. Although, like StrongBad pointed out in his answer, you need to make sure they are willing to cover you even though you don't have a return ticket. A fellow grad stdent tripped and broke her arm before term started and ended up with an emergency room bill of roughly $5000. That's considerably more of a financial burden on you or your parents than $100-200 worth of insurance. And you could end up with similar bills for a bout of food poisoning, or the flu, or a car accident, or any number of accidents. The insurance is even more important if you (like most of us) don't have a lot of money lying around. The cost of insurance is a slight inconvenience, but the cost of an actual medical emergency in the US is a disaster in that case.

Thanks for the response !....One thing I got to know recently is that you can have retrospective referrals or something like that from the long-term insurance company (the one university will provide me). Is that really possible in case of emergency ?

@stringcosmologyapplicant I'm afraid I'm not familiar enough with US insurance regulations to know if that is the case. I do however think it would depend on exactly with insurance company your university uses. I would contact them and ask if that is possible.

You are asking if it is risky not to buy the insurance. In absolute numbers, it is not risky. There is only a small probability that you need it. Also, doctors will offer also their services for a fee in case you need it.
However, there are two things to consider. First of all, if you need medical attention, it is very expensive. For example, if you get a cold and need a prescription for medication, expect to pay more than 300 US-Dollars. Treatment is a bit cheaper if your insurance has a contract with the doctor, but if you don't health insurance, then you can't take advantage of such contracts.
Also, there is always a low risk that some kind of emergency situtation can arise (traffic accidents come into my mind), and the insurance would give you support here. Such cases can easily cost a five-digit amount of money. And this is where an insurance would help you: by allowing you to make a relatively small payment that does not burst your budget, it allows you to have the (relative) certainty that your budget will be fine even in extreme cases.


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PhD in theoretical physics after dropping out of PhD program in Engineering?
I am applying to US universities for PhD in theoretical physics (for Fall 2015). I was earlier an engineering undergraduate student from a reputed college in Asia with GPA of around 8.0 (on a scale of 10). Due to my research experience during undergraduate, I got scholarship to do my PhD in Europe at one of the top-30 universities in the world. But after two years into the graduate program and publishing one journal paper, I realized that I was only doing numerical methods which did not really suit me as I always wanted to do rigorous math and discover new physics. So I left this program (in good standing) to pursue theoretical physics research.
Immediately, I joined the topmost physics institute in my country for research in string theory, cosmology, general relativity. Within a year, I was able to produce three publications in top high energy physics journals like the Journal of High Energy Physics (JHEP) with my collaborators, who are well-known. So these collaborators have provided me good recommendations as well. Additionally, I have good GRE and GRE Physics scores.
My question is how an unconventional profile like mine will be seen by graduate admission committees at good US Universities. Would my engineering background (especially dropping out part) and lack of official physics coursework put me at disadvantage ? How much my four publications would help me in the process ?
Thanks

when you say immature decisions being 16, does this mean you were a PHD student in the UK at 16?  Unless that is the case, I think the 16 years old does not make you immature. What age were you when you went to the phd program and why, is probably more relevant

I was 20 when I went for PhD (16 for the undergraduate). But in my home country, there is very little exposure to pure sciences. I was immature in the sense that I always thought that engineers also make real physics discoveries, which is why I continued my engineering studies into PhD in UK. But then I saw most people doing simulations, and I also ended up doing same numerical methods and simulations. I wrote huge codes for two years, which made it completely boring.

A bit tangent, but i would advise you to be careful about broad statements that engineers dont make 'real' physics discoveries.  It is also still not clear how your home country was so different.  If you went through years of undergrad and still applied to engineering, was it your specific program or the field that did not fulfill your expectation

My home country is poor and there is very little money for pure sciences...so most people discourage pursuing a career in sciences. I always liked physics but I thought I will be able to make original discoveries as an engineer. I would not generalize to every engineer but I didn't see any way of discovering something fundamental while being an aerospace engineer. And there is very little research that is being done at my undergraduate program. I always tried random things to start on and ended up doing programming and numerical methods so I thought a PhD would provide me a better chance.

Also, people switching to sciences after engineering is very common in my country as many students go through something similar as me. Both of my string theory advisors were also engineering graduates (one of them did his PhD in the group of a Nobel Laureate in US).

The only problem I can see with cases like yours is that some people may look at the file and think "This is someone who can't finish what they start."  It is essential for you to communicate in the statement of purpose why you left the old program and why you believe you will complete a new one.

Thanks for the prompt response. But wouldn't my three publications in string theory be seen as my commitment to the physics research. I have talked about my immature decisions in my personal statement. The thing is that in my country pure sciences are not encouraged socially due to lack of good reputed jobs. So most people here who love sciences end up doing engineering.

I think letters from your previous supervisor would do a better job in this front. Your abilities are not in question, your persistence and will to continue could.

Thanks. One of my PhD annual viva examiners has provided me recommendation letters. I was also TA for this examiner during my three year stay in UK.


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Transferring to a Top-10 PhD program in Theoretical Physics from a Top-50 program in US for better job prospects in Academia?
I will be soon joining a Top-50 school for a PhD in High Energy Theory. They have some very good professors who have published top quality journal articles in their area of expertise (even with some Nobel Laureates as co-authors). They are not as famous as Nathan Seiberg, Leonard Susskind, etc. though. I would like to know, given the job scenario in academia (especially in high energy theory), is it worth transferring to a top school like Harvard or Princeton after performing very well at my current school ? I mean, is their any huge advantage in the academic job market to be at a Top-10 school compared to a Top-50 school ?
I do not really care about going to a brand name school as far as my studies are concerned. I just want to make sure that if I work hard and succeed, I do not face problems in getting an academic job just because I did not attend Harvard or Princeton. Academically, my current school is very good too but it doesn't have that IVY kind of brand. My concern is only about the people in the hiring committees otherwise I am happy going to my current school.
Also, I have earlier worked with Professors who graduated from such top schools and they say that famous advisors are like "King-Makers" who get their students well placed in academia after PhD since they have influence in the field. Personally, I have no issues being at my current school if I get good people to work with. Also, is it ethically good to change schools like this ?

Well, better is better, in academia just as anywhere else.  Certainly if you got admitted to a Top 10 program and a Top 50 program then all other things being equal you should enroll in the Top 10 program.  (In fact, even things being only mildly unequal, you should enroll in the Top 10 program.  You should seriously consider the Top 50 program only for serious personal considerations -- e.g. if because you are caring for a family member, you cannot leave your hometown -- or because you have a preternaturally good fit with a particular faculty member.)
But that's not what you're asking; you're asking about transferring later to a top program, which presumably means that you have not yet been admitted to one.  That is not a good plan.  The competition to get into the very top PhD programs is of a roughly similar level of difficulty as the competition to get a post-PhD academic job.  The main difference is that the former competition is more cut-and-dried whereas the latter competition has great amounts of uncertainty and randomness.  In other words, it's actually pretty easy to make most admissions decisions at top ten places: there are certain agreed upon metrics that most or all graduate programs take into account, and the top programs pick from the top applicants according to these metrics.
This has the following important implication: if you applied to the top programs in year N and didn't get into any, it is very difficult to transfer into them in year N + 1, N+2,...The idea of "transferring from one graduate program to another" is already not very standard, and when it is done it is often done to deal with a problem rather than by virtue of exceptional success.  The one exception is that it is common for one to transfer from a master's program to a PhD program.  However, in many STEM fields in the US, the best students just enroll into a PhD program straightaway: their undergraduate preparation is just as good -- or more often, better -- than what American students graduating with master's degrees get.  (In other parts of the world, a separate master's program may in fact be mandatory, so things are a bit different.)  Most American STEM master's programs that I know of are "PhD lite": they are for students are either not as strong, not as prepared, not as committed, or some combination thereof as the PhD students, so getting a master's degree is -- relative to the desired goal of transferring to a top place -- no great distinction.
To be able to transfer from a top 50 HEP program to a top 10 one, you would have to do some truly excellent research at the beginning of your career.  Transferring out of a program in which you've had such sterling success is worth some second thoughts, but if you did this work largely or entirely on your own and the continuation of it would be aided by transferring to a top program: OK, do it.  However, this is very rare, and if you do something that great, then you're on your way to success independently of your transfer plans.
I think that if you spend the first few years in your PhD program with the express goal of transferring out as soon as you can, there is a substantial risk of that showing through as a lack of commitment to your current program, which could really work against you.

I mean, is [there] any huge advantage in the academic job market to be at a Top-10 school compared to a Top-50 school ?

It is an advantage, yes.  The advantage can be overcome by your own work, and if you want a very distinguished post-PhD academic job, then getting a PhD at an absolutely top program with a world-famous advisor is not a golden ticket.  (I know this as well as anyone: feel free to look up my academic past.)  If you go to a top program and do "about average" there, then you will probably not get a top academic job because you will not be getting the top drawer recommendation letter from your famous advisor.  However, that same advisor could help you out getting placed at a lesser institution, or the pedigree of the institution could help (a lot, in some cases) if you wanted to get a non-academic job.  Better is better.

I have earlier worked with Professors who graduated from such top schools and they say that famous advisors are like "King-Makers" who get their students well placed in academia after PhD since they have influence in the field.

The people that the King-Makers make kings were doing pretty well on their own.  A truly eminent advisor can probably place some of their students in very good positions.  But not all of them.  The important thing to remember is that the quality of your own research -- as perceived by the academic community -- is what will get you or not get you an elite academic job.  If your work is superior, it is superior no matter where you are, and the community will recognize that.  If your work isn't that good but is still strong by the standards of the top institution, then having an eminent advisor really comes in handy.  If your work is not as good as many other students of that advisor, then you are not going to get a big career boost.  In some situations, having an advisor who is still well known and recognized by the community champion you as they have never championed a student before, could work out better.

Also, is it ethically good to change schools like this ?

I see no ethical problem with changing schools in this way (although as ever there are more and less gracious ways to proceed); leaving a program for a much better one is easy to understand and I think few people will hold it against you.  But as I said above, effecting this kind of change is just very unlikely;
the real concern is what will happen to you while you are angling for it.  If you are just working that much harder to do your best work: great, and great whether you transfer or not.  But don't make plans or behave in a way which will only payoff if you transfer.  E.g. you might reason that merely doing well in the coursework and qualifying exams is not going to be nearly enough to allow you to transfer to a top program (correct) so that instead you should blow off your coursework while you try to solve the hardest problems in the field (disaster).  Learn to grow where you're planted.

Thanks for the detailed response. I definitely has no personal ambition to go for Harvard or Princeton just for the brand-name. Even some earlier students of a prospective advisor at my current school have been able to get faculty positions at MIT and other such places....but that was 15 years back. Now, the situation in High Energy Theory seems particularly bleak because of very little funding and super-intense competition....only this thing concerns me. But I guess, as you said, my work in any program will decide if I get a position in academia rather than brand name. Thanks again.

Also, I think I would have easily got admission into at least Top-20 programs. The only big flaw in my application was that I come from a completely non-physics background. I do not have any physics degree or a coursework record. I only had multiple high energy theory publications in top journals and good recommendations. So, if I finish coursework at my current school with good grades....wouldn't that increase my chances of getting myself transferred to a top program ? Thanks

"Also, I think I would have easily got admission into at least Top-20 programs." Would have if...?  "I do not have any physics degree or a coursework record. I only had multiple high energy theory publications in top journals and good recommendations." That is an unusual situation.  How did you come to have multiple publications in top journals without any coursework?  To advise you specifically is outside of my expertise: I am a mathematician, and in any given year there are probably zero applicants to the top math PhD programs who have "multiple publications in top journals".

What journals have you published in?  If you have multiple publications in top journals, why are your recommendations only "good"?  What would be better?  Your situation is not quite adding up to me.  "So, if I finish coursework at my current school with good grades....wouldn't that increase my chances of getting myself transferred to a top program?" In my experience: not much.  Grad coursework provides little opportunity for distinction: in many courses, all who do satisfactorily get the highest grade.  And top schools are less hung up on technicalities involving credentials.

I did not do any coursework but I studied subjects like general relativity on my own and then asked many professors for advising me on some research project. With some good fortune, one professor at the top institute in my country (not US) agreed to keep me on a project after I succeeded in working out a test problem. And, the string theory project he gave me to work on proved to be successful for me and I was able to publish two papers in JHEP as I had done a lot of the tedious calculations. I was able work on another paper with the same professor, which resulted in another publication.

And my main professor (with whom I published) gave me a very very good recommendation. I still needed two more recommendations....which were definitely good but not "very very good" since I didn't get to work with them a lot on a research project. Also, my main professor is a brilliant guy but he is very young and not very senior in the community. Actually, all my recommenders were very young and one of my recommenders was not a physicist. I had no other options. With that I did get wait-listed at a couple of Top-20/30 schools during admissions but didn't make it to the final list.

First, I want to emphasize that I overwhelmingly agree with what Pete wrote. That said, it has been observed that the "top" universities produce the majority of our corps of professors (when it comes to the justification though I admit a big chunk of that Slate article rests on anecdotes, and we know that the plural of "anecdote" is not "data"). However, you should not read into this necessarily a causal relationship (as opposed to a mere correlation).
There is not (and can never be) an experiment showing that the same individual would receive a necessarily a better education at a top 10 school; similarly, no one can prove conclusively that students admitted to a top 10 program are necessarily "better" (aside from "on the metrics used to determine admission"). Certainly while one can observe the hiring disparities, no one can really explain "why" (at the very least, it is not possible to tell how much it is down to the quality of the program and how much it is down to the quality of the individual students). With academic hiring the nebulous process it is, there's no way we can just tell you whether moving from your current institution to a different one is, in general, a good idea or not, because statistics, in this case, is a lot less useful an indicator than knowing your personal circumstances. Yes, all else being equal it is probably a good idea to choose a Top 10 school over a Top 50 one; but all else is never equal, except on Econ 101 final exams.

One remark, however: if you are just starting your PhD program and you are already concerned about the academic job prospect because "the situation in High Energy Theory seems particularly bleak because of very little funding and super-intense competition", I must ask "are you sure you want to enter into high energy theory?"
(I confess when I started graduate school the notion of "job prospect" is quite far from being on my radar. And while I am quite happy where I am in my academic career now, and quite happy with how everything turned out so far, I am not 100% certain that, had I known 10 years ago what I know now about the academic hiring process, I would have set a career in academia as my goal.)

Thanks for your response. I definitely would like to work in academia as I love research as well as teaching. And I do not really care about going to a brand name school as far as my studies are concerned. I just want to make sure that if I work hard I will not have any issues getting a job just because I did not attend Harvard or Princeton. Academically, my current school is very good too but it doesn't have that IVY kind of brand. My concern is only about the people in the hiring committees otherwise I am happy going to my current school.

Not going to Harvard or Princeton will not box you out of a job.  Which is not to say there's any guarantee of a job, no matter where you go. - - -  Glad to hear you're happy in your current school.

It would be far worse to get a lukewarm letter of recommendation from a relatively bigger name than for the letter to be written by a not-so-big name.
Try to choose an institution that is strong in research in your field and has a real commitment to good undergraduate pedagogy; then get some experience teaching.  That will help your job applications down the road.

It is even worse if nobody reads your job application because you are not from a big name institution or research group.  The current reality is that faculty searches get more applications than they can possibly read.  I say transfer if you are able; I never heard of anyone achieving that.

@Anonymous: In my field (mathematics), an application from a Top 50 program would certainly be opened and at least briefly scanned by everyone.  If the candidate has superior results, as described in glowing letters from top people in the field, then the review process continues irrespective of the ranking of their institution.  Conversely, a PhD from a very top program does not guarantee anything.  I would be surprised if things were very different in physics: not reading applications is a very poor strategy for getting the best people you can.

I recommend you beware of the theoretical HEP job market. You may want to read http://www.reddit.com/r/Physics/comments/271apx/a_view_from_an_exstring_theorist/
and
http://backreaction.blogspot.com/2015/06/the-plight-of-postdocs-academia-and.html
I really don't want to discourage you learning these stuff. But there are reasons why people keep warning beginning grads to stay away from theoretical HEP these days...

these two articles seem quite depressing but also realistic as I know many theoretical HEP colleagues in the same unfortunate situation. Btw, don't know why -1 here.


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In experiments involving study participants, why are some studies allowed to only have a small number of test subjects?
I noticed that in my field, studies involving testing with human subjects often only show a small number (N>=10) of them. While I understand that researchers are often limited on funding and time, I always thought studies like that would require a certain minimum of subjects far greater than that.
Different sources I found (e.g. this one p.3, this sample size calculator, or Wikipedia) seem to support that impression.
My field is audio signal processing, and the studies that caught my attention were about speech intelligibility, hearing comfort and other measures related to human hearing.
My question is:
Why do some studies only involve a small count of subjects when statistical theory suggests a high number of participants is required to make meaningful assertions?
(I assume that there is something I missed or something that got mixed up in my head, and I'd really like to find my error)

Potential safety issues, new protocols that could have unforeseen problems etc., may make it necessary to perform tests on a small scale. Even if no harm would be done by going straight ahead with a large scale trial, you don't want to find out later that the results are worthless due to procedural errors in implementing the protocols.

Okay, that does make sense to me. It seems to me, though, that large-scale trials are not carried out at all, and conclusions are drawn from the small-scale experiments. I am wondering why this is legitimate.

This is probably a better fit at cogsci.se, but as it is essentially my field I will chime in. Individual differences in psychoacoustic studies are typically pretty small for highly skilled and trained individuals and the point of the studies is to determine the limits of perception and not what percentage of the population can achieve those limits. Therefore we find 1-5 great subjects and train and test the hell out of them. You typically can learn more from 100 hours of testing one good subject than testing 100 subjects for an hour each.

Because then you get to justify the traditional "Further studies are needed to confirm these results."

"...only show a small number (N>=10) of them." You mean "N<= 10", right?

Is it possible that some of these studies are just using a subset of data taken in a larger study? For a medical example, a large study looked at the effects of drug X, but a small study looked at the effects of drug X on diabetics. The larger study may not have been explicitly targeting diabetics, but there is still some relevant data there for analysis.

Who would disallow it? Funding agencies, the IRB, PIs, journals?

Large study groups are expensive (time, resources to set up and collect results, paperwork to get permissions, and so on). Better a small study (with perhaps not-so-clear results) than nothing.

Although large samples produce more robust results, small samples are not completely devoid of usefulness - they're just more likely to be wrong. As long as the reader keeps this in mind, there's nothing fundamentally wrong with publishing these small-sample studies.
Further, sometimes you just cannot get enough samples to make an assertion with confidence. Examples:
GW170817 was a one-of-a-kind neutron star merger event. Since the rate of neutron star mergers isn't well-known, one could easily wait another five years and not get another sample (plus you'd need hundreds of samples to make the kind of statements you're looking for).
The Berlin Patient - there's no cure for AIDS. Even if this single case were a fluke, it's still worth reporting since it's a signpost telling researchers where to look.
Habitability research - The question of whether aliens exist captures the public imagination. Like it or not, we have to approach the problem from what we know, and we know only one planet with life (i.e. sample size of one). You could of course just decline to work in the field until we've discovered several hundred alien civilizations, but then you could be waiting forever. Plus with no idea what to look for, observational astronomers would have a much harder time finding these civilizations.

Small samples are more likely to be wrong about the population, but an N-of-1 study reliably tells you about that individual.

In usability research, just 5 participants will reveal about 75% of the problems with a system. This seems to fit very well for qualitative research (so perhaps the hearing comfort studies you mentioned?). From my own experience of running studies with 8-32 participants, it only took running the first few participants before every subsequent participant felt like a repeat.
Sure, you might not be able to get statistical significance with 5 participants, but you can learn a lot.
Figure taken from Nielsen's article Why You Only Need to Test with 5 Users.

Somewhat in the same direction: if you consider a sensory panel (smell, taste), you should not start with < 8 panelists because of the biological variety in smell receptors across humans. (And you won't be able to afford many more...)

Of course this depends a lot on what you're after. If you are looking for differences or some other effect within an individual, then your sample size are measurements within the individual rather than number of individuals. In such scenarios it is legitimate to study only a single (or a few) individuals.
Also, if your individuals are not studied per se but act as "instrument" (testing answer by @AustinHenley, or setting up a sensory panel, i.e. you use N individuals to smell/taste the effect of something you do/produce) you need a number to cover most of the important general variation we have in the population. But that number actually isn't that large because typically only people who are good at the task at hand will be used. I.e., smell-blind people do not apply for a sensory panel in general, you only need to cover the variation in receptors you encounter in people who are good at smelling. And that are far fewer than, say, the number of people you'd need to look at to find out which proportion of people are good at smelling, or the number you'd look at in order to be able to predict, say, the probability that a randomly chosen unknown person will like the smell/taste of what you produced:
If you need to make conclusions about a population or about applicability of your findings to unknown individuals of a population (if we train our method on an individual, this is how well it will do), you need to representatively cover the variability in that population, and this requires large sample size.

For the population questions, I fully agree with @Buffy's analysis, but I'll go a bit further about possible reasons.

The maybe most scary (to me) reason is that it is IMHO perfectly possible/far too easy to publish studies with low quality due to far-too-small sample size.
Note that I've been working in a life-science field, i.e. close to where we have lots of reports about studies not being reproducible since years, and at least in my sub-field not much of an effect on the sample size.
One particular problem I see with small sample size studies is not scientific (as in limitations of conclusions that can be drawn) but political. The "politics" of academia focuses very much on novelty. This basically means that once a small sample size study is published, any larger follow-up study has to present extremely good arguments to overcome the "this is known already" bias in funding.
This means, in addition to being uncertain, small sample size studies may prevent getting certainty.
In (industrial) experimental design it is often recommended to start with a preliminary experiment using, say, 1/3 or 40% of the available resources. Then do a preliminary analysis and if necessary re-adjust the allocation of the remaining resources accordingly.
This takes time and means effort. However, if the preliminary results are good, they can be published. The follow-up study will then potentially face a lack-of-novelty hurdle to publication.
Master's and PhD theses by definition are the work of one student. This limits how much work can happen in one study. And it pushes towards experiments that are inconsistent in the long term: students cannot be abused as lab robots (which would help getting together good sample sizes - but good lab technicians are more expensive...) as they need to contribute scientifically. One of the easiest ways to do that is to improve the experiments over what has been done before - leading to large numbers of small sample size studies/fragmented series of experiments.
The requirement of "own work" sometimes causes students to not speak openly about their project and not seek advise. Every so often that leads to flawed experimental design and/or too small sample size and this is realized only during data analysis (or not at all). But then it is often too late to do anything but try to rescue the existing data. And rescued into a paper it must be, because otherwise the student won't have the paper they need.
I see another potential conflict in mixing the evaluation of scientific work (as in grading the PhD student's work) and arriving at scientific findings:

if a student in their well-planned and well-conducted study finds the "desired" effect, that implies both that the student did their work well, and we have a scientific advance. All is fine.
However, if things don't work out nicely, things are much more difficult: Was the failure due to the student not working well (I come from a wet lab field)? And/or is there no effect? In other words, the student not finding an effect has to put in much more effort in demonstrating it is not their fault.

Now consider putting a set amount of effort either in n underpowered studies or in 1 with good sample size. If the one with large sample size fails, you don't have a single paper*. If a small sample size study doesn't find an effect it is simply not published, and you move on to the next, because it is usually too much hassle to make a paper publishable with negative finding. But keep in mind that small sample size papers are not only underpowered, but they also "provide" a high "chance" to produce false positive findings (i.e. overestimate effect) - and that means a paper.
Our brain tends to underestimate the effect of chance. This means without doing the statistics, we're likely to intuitively underestimate chance and be overconfident in our findings.
There are studies where it is practically speaking impossible to obtain anything close to the required sample size**. And there's nothing wrong scientifically with case reports and small studies as long as they are clearly indicated as such, and the conclusions take the required caution and limitations are clearly stated.
Often, it is also practically impossible to obtain representative samples. I'm still OK as long as a) limitations are openly stated, and/or b) even applicability is checked by plugging in reasonable guesstimates for prevalence/incidence/class frequencies to at least give a critical thought to suitability for the application in question.
However, I see far too many studies that needlessly "rescue the world on the basis of 3 mice" or that work on, say, 20 samples of tumor tissues that are anyways cut out of patients with a disease that is neither rare, nor is the tumor volume small, nor is all the tissue needed for correct diagnosis in order to properly treat the patient.
Finally, I consider it the worst possible waste of experimental effort (and that's even worse if test subjects/animals are involved) if a study is so small that a back-of-the-envelope calculation would have discovered that even in the best case no practical conclusion can possibly be drawn.
(e.g. reserving 4 independent test patients in development of a medical diagnostic [pos/neg for some disease] out of your 20 patients. Assuming all 4 are correctly classified, this gives you an observed accuracy of 100 %. But the 95 % confidence interval for accuracy ranges from around guessing to perfect.)

* real life example:

I've met a PhD student who
was working with a ≈ 500 patient sample size in my field. Measured them all, found there was a flaw in the design of the measurements (not properly randomized order of measurements, thus strictly speaking drift in time of the measurements could not be excluded as cause of the observation - which however looked like real effects from a physical/spectroscopic point of view). Realized this, and re-did all the measurements. Did not find the effect which was expected from long experience of the supervisor with similar situations and preliminary experiments. It is not clear whether there is truly no effect after all, or whether something else went wrong with the experiments (non-negligible risk for what they do), or both.
Same field, other university, other students get their PhD on the basis of, say, 20 patients. Not randomized, never thought about experimental design, not to speak of limitations of their study.

I'd judge student 1 much better than students 2 in terms of the scientific work they did. But they'll have to face a struggle to convince their committee of that: the committees of 2 clearly were not aware of the limitations, nor were the referees of the papers. So students 2 happily publish multiple papers in the time where student 1 struggles whether their study can be published. And student 1 did admit to a mistake, so there's evidence of student 1 not working well (they did make a mistake after all) - whereas there is no such evidence in the studies of 2....
** I'm also fine with the practical limitation that in many interdisciplinary fields if you need significant work of others (in our case, e.g. reference diagnoses by pathologists reviewing every single of our samples) those others may want to see preliminary data published in order to make sure they don't waste their effort with people who don't know what they are doing and/or are not serious about the application.

Excellent +1 (more if possible). I always told my students that a negative result is just as valid scientifically as a positive one. You are seeking knowledge, not a pre defined result. If the "effect" doesn't exist, you need to know that just as much as when it does.

The majority of this answer is about the population, but the question is why small N studies.

@StrongBad: many of the small N studies I see do draw premature conclusions about populations or about the generalization performance to unknown individuals. So if that's not an issue, small N is not an issue but appropriate. However, of the small N studies I see, there are few where that small N is appropriate...

@Buffy: thank you. And do go on telling your students that "no effect" or "does not work" are just as valid scientifically. And please also tell them that that happens far more often than they'll see in the literature (unfortunately - but I think to some extent also unavoidably in practical terms). It was quite an eyeopener for me when someone from a funding agency told us in a project meeting that they wouldn't consider funding project they though had > 20 % chance of success! The academic inside point of view was that most projects are successful...

I will go out on a limb here and suggest that you are correct. Too many studies are too small to have meaningful results. I fact a google search for [scientific studies not reproducible] turns up some scary results. One is that only 10-30% of studies published in journals can be replicated.
There are many reasons for this, but poor research design is a main culprit, including too-small sets of subjects.
As to the reason for the small sample sizes you can point to both money and time. It takes more money and time to sample a larger set in all but trivial situations. But it can be hard or impossible to get a larger body of subjects for many studies. The potential universe of subjects may be widely distributed in space but sparse within the larger population. Sometimes many factors may be required for acceptance, leading to rejection of many. Some studies may just run up against opposition from the population due to many factors, including simply that it takes effort on the part of a subject.
In addition to the size factor is that many studies rely on using students at the same university as subjects. These folks are not representative of the population as a whole unless the population itself is defined to be university students.
Another problem with samples is that the subjects are always assumed to be "randomly" chosen from the overall population, but it is very difficult to assure that in many cases. This is the problem with using university students, in fact.
Small sample sets are perfectly natural for preliminary studies that can give direction and provide refinement to the design of a larger study. But, as you suggest, it is hard to extrapolate results from a small sample to a large population if that population has much variability.
Moreover, small studies cannot, by the nature of statistics, capture subtle effects. If you are trying to determine if more "mumbles" have characteristic "A" or characteristic "B", then a small sample size of "mumbles" will work if, indeed, the actual population breakdown is 70-30, but statistically unlikely if it is 57-43.
For reasons like the above, many researchers are moving from a standard 95% confidence interval in studies to, perhaps, 99% (or more). This helps weed out many of the design issues that cause the problem of non-reproducible studies. But that is risky for students who want and need some results to put into a dissertation and are limited in both time and money. But while small sample size is fine for initial, exploratory, studies, it is not for determining the state of reality.

The field in question often doesn't care about the population but rather about the limits of the population/perception.

Not all studies are quantitative.

@AustinHenley, true enough, Statistics aren't always the tool of choice. But that deserves a separate answer with a complete explanation. I think the other answers here are talking about statistical studies and assume, as I did, that the OP was interested in that, specifically.

The main reason that psychoacoustic experiments only utilize a small number of subjects is that the goal is generally not to determine the average performance of the population, but rather to characterize the limits of perception. With an N of 1, you obviously do not know if you have measured that individuals limit of perception, or got lucky and measured the limit of perception of the best individual. Based on the history of the field, from a bayesian vantage, there is a ridiculously strong prior that the first author of a study will be the best trained and most highly motivated subject and have the best performance. There is also a strong prior that with sufficient training and motivation that a substantial percentage of young healthy subjects can achieve similar performance. Studies typically conclude that humans can do task X at a minimum of level Y. There is so much data for each of the few subjects, that one can conclude that each subject's performance is highly unlikely to be from chance and that it actually represents performance. That said, it tells you little about the performance of a random individual.

... in other words, you give an example of a field that is not (yet?) interested in exploring the variance (as needed in performance of the random individual). Good to know.

@cbeleites the question specifically mentions audio signal processing so I thought sticking in that domain made sense.

@cbeleites There are plenty of things to study, in any field; if one is doing science, one generally tries to study as few things as possible at once, to avoid confounding factors. You'll be happy to hear that in the particular case of psychoacoustics, there's been a huge amount of study of variability over the general population.

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text:
Conference paper rejected without any fault in algorithm
I am working on a hard problem in computer science. The problem is NP-complete. Untill now, the fastest algorithm for this problem runs in $O(3^n)$ time and I came up with an algorithm with a time complexity of $O(2.82)^n$. Yet the paper, in which I described my approach, was rejected in three A* conferences. I am wondering why.

First conference: They asked why I did not compare my algorithm with
algorithm X. They appreciated my algorithm and have not found any
fault with it.
Second conference: Now I compared my algorithm with algorithm X.
They asked me why I did not compare it with some parallel algorithm Y.
Again they appreciated my algorithm and have not found any fault
with it.
Third conference: This time I compared my algorithm with algorithm
Y. They did not find any fault with my algorithm and said that it
still is exponential and that for large input number it will take
much time. The paper was rejected. But isn't 2.83^n a clear
improvement over O(3^n)?

I'm at a loss. What should I do next to publish my result in a good conference?

The reviews you get from the conferences should tell you why your submission was rejected. It is quite common for good papers to be rejected from top conferences, as the standards are very high. Usually this is because the paper is deemed to be not interesting enough (or out of scope), in which case you should find a less competitive (or more relevant) conference to submit to.

Yes I got the reviews. No technical input, I mean they did not raise any question against my algorithm. They are questioning that my algorithm still exponential. Another comment was to test my algorithm for larger inputs, whereas the state-of-the-art paper  took also less input. The experiment is tough for me because of infrastructure. If we give input $n$ actually it converts to $2^n$, its huge and I failed to test  for $n=26$ or more. Thanks for your advice. I will go for A conference now.

a couple of months ago you posted this question: https://academia.stackexchange.com/questions/83807/ways-to-publish-new-result-for-np-complete-problem-without-proof  where you able to find the proof? if not, maybe that why it was rejected.

Oh yes, I have proved it. But that was one imperfect algorithm for my problem whereas my present paper is an exact algorithm. I have also defined time complexity and correctness proof on my present paper. the reviewer did not raise any question about that.

Since you are describing an algorithm paper, I assume you are submitting to algorithms conferences, and the "A*" description refers to the CORE ratings of CS conferences originally developed by the Australian Research Council.  The only A* conferences in algorithms are FOCS, STOC, and SODA. I've served on the program committees for all three.
These three conferences are extremely competitive, and standards for acceptance are extremely high. It is not enough for your algorithm to be correct. It is not even enough for your algorithm to offer a significant improvement on the state of the art for your specific problem. At STOC and FOCS in particular, papers are judged on their likely impact on theoretical computer science research beyond the scope of the specific result. For algorithms papers, that means either that you're describing a significant advance on a problem of central interest to the field, and/or that you are introducing new techniques that are likely to generalize to many other problems, and/or that the PC finds your result both surprising and technically impressive.
I would not expect these conferences to accept a paper that only describes a faster exponential-time algorithm for an NP-hard problem. We've seen lots of those before; yet another one is not that surprising. Unless you are proposing a strong general technique, or the specific problem you address has resisted significant progress for a long time, I would recommend aiming for a lower-tier algorithms conference: ESA, ISAAC, COCOON, WADS, LATIN, ....
All the advice in the other answers still applies when submitting to those penultimate-tier conferences, of course. It's still not enough for your algorithm to be correct. You still need to clearly explain your precise contribution and its importance to the research community. You still need to give a thorough comparison of your algorithm to the state of the art. You still need to convince the PC that they should trust you and care about your results.

thank you for advice. I will submit it to some low-tier conference. I will have to make experiment section better.

Whoever said "Shoot for the moon, for if you miss you will land among the stars" was probably really bad at orbital mechanics.

haha right @corsiKa but its nice quote

"Shoot for the moon, for if you miss you will drift among the stars" then, @corsiKa ?

@sgf "If you shoot for the moon and miss you're going to drift in a slowly decaying orbit until you burn up on reentry."

@corsiKa https://www.youtube.com/watch?v=LHvR1fRTW8g

From reading your question, I'm guessing you failed to articulate the significance of your contribution and problem.  One aspect that you need to understand is the interest of the community.  Take the matrix multiplication problem as an example: when a recent paper (2014) claimed a 'small' improvement in the bound by a few decimal places, it was big news.  Why?  Does your problem fall in this category?  If not, then it will be hard to get into top conferences.  Another problem is that your slight improvement may be 'obvious' to the community, and hence, it is not interesting.
In summary, rewrite the significance of your problem and discuss why the 'small' improvement is very significant.  Why should the community care?  Was the method used innovative?  Does it have wide ranging application on other NP-complete problems?  If you can't make a case, then it is time to look for lower-tier conferences.

Yes, it has wide ranging applications. My problem is weighted set partition problem.

Thank you very much, I will take care those points you mentioned and submit again.

Since I do not know details about the problem you're working on, the reasons come to mind can be various. But based on your question and comments, I think the reviewer tells you that your improvement is not significant.
If they require you to test your algorithm with bigger inputs, that means they are looking for a reason to pick your algorithm over the other one. Sometimes, even your algorithm has slightly less complexity in terms of running time, the first described algorithm might be a standart and neat one.
Another reason might be that the algorithm you're competing with is just a naive algorithm to give solution to the problem. Maybe authors of that paper prove some other result.
Not every correct algorithm is to be published, and not every improvement is significant. For instance, merge sort was developed in 1945 with worst-case time complexity Nlog(N), and shellsort was developed in 1959 with the same worst-case time complexity. But one cannot argue that shellsort is insignificant.
All in all, to answer

Please share your advice what to do next to publish my result in good
  conference.

Try to write what do you improve and why would it be important for scientists to know about your improvement very clearly. If you're not convinced it is a considerable improvement, then there is a good chance that audience of conference will not either.

My problem is weighted set partition problem. Thank you for advice


text:
Refering to the data of another study as a source of data for you work?
I was wondering if it's OK to use the data presented in the form of Tables in other publications and cite them as the source of data? Like doing new analyses on these data? Should we ask for permission from the authors or just citing them would be OK?

It is absolutely okay to use data from another publication for your own analyses.  Indeed, this is one of the main reasons why often raw data must be made public (unless there are specific contractual or ethical reasons not to). Once the data is published it is in the public domain that there is no requirement to ask permission and the original authors have no right to object to you using it - if they wanted other not to use it, they shouldn't have published it. You do need to cite them however.

I feel like there could be some caveats here. For example, I work with spatial forestry data that is accessed via data sharing agreements. So while I can report results based on my analysis, I’m contractually not obligated to share the raw data without explicit consent. But, I believe that if the data itself is published in the public domain, then by all means it is fair game.

@GrayLiterature: "contractually not obligated to share" or "contractually obligated not to share"?

You are right - there are situations where it is not possible to make raw data available. The point that published data is available for all to use holds though.

And, while you can "use" the data, you can't republish it without permission of some sort. Do you have a reference for "Once the data is published it is in the public domain"? I think that is probably wrong.

I don't have a reference. But we certainly re-publish data all the time. Every article we publish has some re-publishing. As far as i'm aware, copy-write applies to the figure or table, but not the data within it.


text:
Publishing thesis as a book
One of the answers here says that some researchers in humanities publish their thesis as a book. Could the same be done for example in physics, chemistry or math degree?  By book I mean the whole thesis, not just a handbook with selected material.
And if it is possible - could the thesis on which you would defend your degree be written in a book format, i.e. be ready to go to the print shop immediately? Or do supervisors and reviewers expect the paper to be just a "big article" and having complete book in front of them would confuse them?
I also suppose that the book should not be printed(at least in many copies) prior achieving a degree, correct me if I am wrong.

In mathematics this is also possible. I myself published my PhD thesis as a book in a Springer series, and I know of people who published their thesis in the Memoirs of the AMS series. Note that all these still require a refereeing process, so typically the published version will be (slightly) different from your final PhD thesis.
This publication is separate from the Dutch tradition of creating proper printing-press copies of your thesis for distributtion to the reading committee, colleagues, friends, family, which could already considered to be a book (one typically obtains an ISBN). In my case that meant that I had to make only few changes to the layout of my thesis to submit it to Springer; basically adapt to their style.

Definitely don't print it before achieving your degree, in case you have to make major corrections (in which case the book would be a wasted expense).
In the UK, at least, it's usual for the final copy of a PhD thesis to be bound as a book - so in some respects, what you say about "ready to go to the print shop immediately" is already surpassed. However, that is not to say that the internal format of the work is that which would be expected for a normal book, and I imagine that this --- as well as perhaps writing to be accessible to a slightly wider audience --- is what is normally involved with somebody publishing their humanities thesis in book form.
The question that you perhaps need to ask yourself (or better explain to us) is: Why do you want to do this?

The reason why to do this for me is to make thesis more accessible. Making it available online achieves way more in that respect, but having a book also contributes a little. Also, it makes some sense to me since if you already have your thesis written - converting it to book format seems logical step towards making it bigger thing in terms contributing to knowledge. After all when students want to get some information they usually looking/googling for a book(!), not an article. Of course it depends on the topic, but I can think of plenty topics that in some way "asking to be a complete book".

Nobody reads thesis anymore, nobody reads a whole book. In CS, at least, your contribution should be spread in some specific papers published in conferences, journals, etc. People read those. It doesn't really count for CV (looks fake) and converting to book format is time consuming, in most cases. It doesn't make financial sense either, books doesn't sell that much...

At least in some German universities, it is required for the thesis (after all the amendments) to be published as a book. This applies to all disciplines, not just humanities. So it is certainly possible but definitely wait until the final version is accepted.

I know of several people who have done this in physics. In each case, the book was an exact copy of their thesis (right down to acknowledgements and appendices). If I remember correctly, there are some publishers which will publish any thesis, you just have to pay for the first n copies (where n is an integer I don't remember).