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Is it considered cheating to use answers I remember from videos I studied?
This question is for those who are familiar with the format of CompTIA exams. Last week I took a test (and passed) which had two performance-based questions that I already knew the answer to. I had seen them verbatim on a recorded video series provided by my school, and my professor went over them with me in class and explained it. On Reddit, I saw posts saying to pay attention to the recorded video series in my class and to memorize the questions because they are very similar to the exam. So I had a feeling that they somewhat might show up on the exam but not 100%. Is this considered cheating?

Put yourself in the shoes of the instructor. What better way to make sure your students actually study your material than to regularly include some worked examples in the test?

@Stephan: Note that CompTIA is a standardized test; the instructor almost certainly did not have control over or inside knowledge of the exam.

Does this answer your question? https://academia.stackexchange.com/questions/178448/did-i-cheat-on-an-exam-by-knowing-a-solution-in-advance Or this one: https://academia.stackexchange.com/questions/112239/what-to-do-if-i-have-seen-an-exam-before-i-have-taken-it

CompTIA tests are also randomized ON THE SPOT by the machine. You didn't get the same test as the guy sitting next to you. You got REALLY LUCKY though, but this is definitely not cheating.

Ultimate cheating life hack: store all the answers in your head so you can't be caught and they can't be confiscated!  Professors hate this one trick

As my old teacher used to say "You're only cheating yourself" - key question is whether or not you understood the answer you were providing? A better question might be "Was the instructor cheating?"

No, this is not cheating. It just means you did a great job studying. On most tests that I give, there will be at least a few questions that the students (those who are paying attention) know will be on the test. Often, I telegraph those, like "this is super important" or "you really need to know this for the test."
Similarly, when I was a student, professors would telegraph questions like that to me, both in undergrad and grad school (e.g., qualifying exams). Paying attention, studying, and correctly predicting a test question, is not cheating.
When I help students study for actuarial exams (similar to CompTIA exams) or the GRE, we go through lots of old exams. We figure out which types of questions get asked every year, and make sure the student is able to answer those. Later, my students often report back that at least one thing we studied showed up verbatim on the test.
Lastly, imagine the situation when someone prepares for job interviews. It's very common to try to guess what questions you might be asked, or to do mock interviews with others who have hired for similar positions before. I would argue that part of what's being tested is whether or not you understand the material deeply enough that you can predict the questions. If so, you deserve to get those questions right! Good job!

No ethical problem it sounds like. The nature of the exam type is well known. That nearly identical questions showed up just means they did a good job prepping you. That said, if you do feel not great about it, you may consider sending a note to the people who run the exam noting that those specific questions are available in the wild (although there are risks/downsides to that).

Comptia almost certainly knows the questions are in the wild. Its been a while since I took a Comptia test, but when I did I had to actively avoid places that claimed to list the exact questions with the exact answers based on actual test takers. And those are the ones that are open about using the exact questions. Study guides for those types of standardized tests are supposed to use questions very similar to the real ones.

It is not uncommon that the exam problems are taken from textbooks or copied from the exam materials from a few years ago. Thus, if you encounter problems that you have already see, this might be a proof that you studied hard. Also, most exam problems are "typical" ones, that is the goal is not so much solving the problem, as showing that you know the method that solves it. Thus, if you feel that you understand the method (rather than copying solution by somebody else) you are not being unfair.


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Collaborators write their departments for my (undergraduate) affiliation
I am an undergraduate student in the medical field. I have taken part in writing multiple articles with professors from different departments from my Uni. The way I see it, my affiliation should be Faculty of Medicine, University of X. Whenever I've been directly asked for my affiliation, this is what I provided.
For some articles, I did not get to proofread my affiliation before submission, and my professors filled in my affiliation as their department. Some articles have already been published, some are accepted, some are pending a decision. I have some articles with Faculty of Medicine, University of X, some with Department of Gerontology, University of X, some with Department of Dermatology, University of X, and some with Research Group for Great Ideas, University of X.
The name of the University is always correct, but I've been assigned to multiple departments, while technically being still an undergraduate. Can this hurt me in the long run? Should I raise my concerns with the authors of the papers? I don't know whether the department affiliation is important, or would be seen as petty.

It might have been important in the old days, when readers wanting to contact you would write a letter and mail it to "Your Name, Department of Gerontology, University of X".  If you weren't really affiliated with the Department of Gerontology, the person who sorted the incoming mail for that department might not know who you were, and the letter might not reach you.  These days, of course, they'll just use email and the issue doesn't arise.

If you do not have an opportunity to proof and approve manuscripts you have co-authored before they are submitted, then that's an issue in itself.  But if your only objections are about affiliation statements, then it's probably not something to make waves about under your circumstances.

I cannot see a situation where this would hurt you. Especially as it is uncommon for an undergraduate to have multiple published articles. Having these will by far outweigh any negatives you might think of.

Don't worry about it. As an undergraduate your affiliation is unclear anyhow. You could reasonably argue that for the duration of that project you were part of that department. At the very least, you can consider it as a welcoming gesture from those professors, that they consider you (temporarily) part of their department.

Agreed.  Along these lines, I am also inclined to suspect that the faculty the OP is working with view the relationship quite differently than the OP does.  "Collaborator" suggests a relationship between peers, and few faculty view undergraduates as their academic peers.

I don't see an issue as long as the university is the same. With a different university, it might be different:

Someone meeting you thinks you went to the same school and is (negatively?) surprised to learn, that you went to a different university.
Some universities get money for number of authors on published papers. They might try to use your wrong affiliation to drive their money up. This is not right and might hurt your alma mater.
If there is a scandal or misconduct with one of your collaborators, being not in the same university emphasis the distance between the you and the collaborator.

My thinking exactly. In many academic systems undergrads aren't formally associated with any department anyway, so at worst it's a white lie. I am struggling to see any possible negative consequences, for either you or your collaborators.

Unless someone is specifically collaborating with questionable external institutions on purpose, or something, it's no more likely for a collaborator from another university to be involved in some scandal than it is for a collaborator from the same university to be.  So #3 doesn't really make sense.

Clinical scientist here. This is good question!
First of all, congratulation on publishing as an undergraduate.
I would see this as beneficial, especially when recruiting you!
In clinical medicine, it is very important to demonstrate that you can work with other departments / disciplines. Cross-disciplinary / multi-disciplinary treatment is an important aspect of modern medical care. You demonstrated that as a prospective scientist, why would it not be the case in clinics?
Good luck!
PS: Your case applied to me, as well. As an undergraduate, I published with numerous different departments (mostly case reports when rotating during my final year). For me and some colleagues, this was normal. Assuming that you were involved in case studies, it is even more normal. The department that treats the patient is your affiliation in this case.

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Professor previously wrote letter, and now he's not responding to my emails
Last year I applied for PhD programs. I got together four letter writers two from my current MA program and two from a previous MA program. I was rejected from every PhD program that year, and I was devastated but not deterred. Now I am trying again and one professor who wrote me a letter last year, is not responding to my emails. Nothing has happened between last year and this year that would change his opinion of me and he hasn't responded to my emails about other things (for example what do I make of last years rejections?). I will also add that one letter writer didn't get back to me for some time before agreeing. All of these things make me unsure of all of this. What do I do?
I have been asking this professor for about a month and a half. After three attempts I went to the administrator in my department. I'm worried it was a bad idea but all I can do is stop before it gets too much of a problem.
Last year I applied to ten schools but I'm in the humanities and I have been repeatedly told that it likely has to do with playing the odds and finding a program that is a good fit. I have complete confidence that these professors themselves know that and to be honest I'm not too worried about that.

"Nothing has happened between last year and this year that would change his opinion of me." You were "rejected from every PhD program that year."

Would an option be to ask for recommendations from more people, even if they are not from academics like an employer?

There is a lot missing here to give anything but an "it depends" answer. How many PhD programs did you apply to? Just how many emails did you send the professor? Are you still at the institution of your MA program, and do you still have contact with the professor? Do you still have the same email address (my institution blocks them after 6 months)?

For how long has this been going on? Just this summer?

Some people go on vacation during the summer.  Maybe the professor will not read his emails until he returns in the fall.

GEdgar, that's comforting but it still doesn't explain the previous questions that I emailed him, that he didn't respond to last spring. I will add that he agreed to write me a letter last year around this time of year (summer), but this can by explained if he went on vacation this year but not last year.

@SteveBerk Just because someone has agreed to provide letters for you for one cycle does not mean they have committed to you for subsequent cycles. While it is common for advisors and collaborators to continue to provide support letters (often for the length of your career for advisors), just some random professor who you interacted with is not the same, and they likely have a whole host of new, recent students who have asked them for letters. I suggest getting someone else who is more current.

Some students may believe that professors just sit in their offices between classes, but I assure you it's not true.  A typical professor, if such exists, will have teaching, service, and research obligations, of which teaching might be about one third of the professor's time.  Class time might be a third or less of the teaching time; the rest being preparation and grading.
You say you've applied to ten schools.  If the professor is like me, that means he has already written ten letters, each tailored to the particular school.  And you are not the only student asking for recommendation letters.
The comments suggest several reasons for failure of communication, including things like vacations and changed email addresses.  From the professor's viewpoint, those ten letters might be construed as fulfilling the obligation the professor took on.  (Or not; I can't read your professor's mind.)
No matter what the reasons, take the advice given by Ricardo Cruz in the comments.  Find more recommenders.  You say you are currently in an MA program.  Probably more than two faculty members know you.  Does your department chair know you?  How about other faculty in your prior MA program.  Employers or others who know your work?

Professors work differently. Some are very respondent to emails; some are clearly overwhelmed by the volume they receive. They also write LoR differently. One LoR writer clearly told me that they just use a word template and then swap some words and add changes only when they have strong personal connections (so marginal effort for new letters very low). Some professors tailor-make their letters much more. Some are basically unreachable during summer even to their own advisees.
It sounds like indeed you need to find a different recommender, or at least treat this certain professor as a backup. Obviously, you can try chasing them down somehow if you know they might be on campus. Going to the administrator other than to find information on where this professor might be (on vacation?) might be a bit too much. Find someone else if you can't wait after summer. I was in a situation where one letter writer even after agreeing to write it did not submit a LoR within deadline, so I had to swap them out for a different one.

I personally don't think getting rejected from programs has that big a chance of them thinking less of you -- most people should be content with the fact that the academic life is full of rejections. Time can both work for you and against you -- indeed this professor might have forgotten much about you, which seems like a probable reason for the current situation, but they also have a ready-made draft of LoR that seemingly they can just rehash.

A quick informal enquiry to the department admin (or another prof) seems fine to me: "Hi, do you know if Prof X is around this summer? I wanted to ask him about a letter." It is entirely possible that they're on sabbatical, medical leave, etc.
I wouldn't make it into a whole thing though: "Dear Dept Chair, I am writing to complain that Prof X. has not replied to my email..." is way, way too much.

@Matt Yes I agree. Perhaps not very clear in my original post, but I intended to express that going to the admin to find the current status of a Prof is more than fine.

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In PhD applications, how should I deal with a MSc supervisor who gives unfairly negative recommendation letters?
I am applying to some PhD programs and need three recommendation letters. Usually, the most important one is the letter from an MSc supervisor.
The issue is that my MSc supervisor is very strict and has a strong personality. He has the mentality that "I invest in MSc students, and when they finally get up to speed, they leave me for a PhD elsewhere." This has made him very upset.
To prevent this, he blackmails students through his letters of recommendation (LoR). For example, one of the people from our lab applied to several universities but was rejected by all of them because of his LoR. This person was only accepted by a university where the potential supervisor closely knew my MSc advisor and was already aware of his personality.
I asked him for an LoR, and he wrote one for me. However, I know exactly which weaknesses he picked on, and he exaggerated them enormously.
Basically, I think I have three options if I don’t want to do a PhD with him:

Exclude him from my referees.
Include him as a referee but provide the other side of the story in
my Statement of Purpose (SoP) to counter any misrepresentation.
Include him as a referee and personally talk to potential
supervisors to explain the situation.

Option 1 seems like a big red flag. They will definitely ask why I didn’t get an LoR from my MSc advisor. They might even contact him via email, and if they do, he would likely say the same negative things that he would have written in the LoR. If that happens, it could be even more detrimental. I would need a reasonable justification in my SoP to explain why I didn’t get an LoR from him.
Option 2 is a bit tricky. It’s almost impossible for a student to criticize their advisor without seeming like they’re making excuses, and faculty often have an instinctive aversion to such complaints. The only way this could work is if the committee or potential supervisor is already familiar with my MSc advisor’s personality through another source—which, unfortunately, is not the case for most of the supervisors I’m applying to. They don’t know my advisor at all.
Option 3 feels quite unprofessional, to be honest.
What do you think I should do in this situation? Are there any other options?

"applied to several universities but was rejected by all of them because of his LoR" -- how do you actually know this? I don't think that the admissions committees will have shared this kind of information with anyone.

‘[H]e blackmails students through his letters of recommendation (LoR).’ That’s one hell of an accusation. You do have evidence, right?

@Aruralreader what kind of evidence do you expect? If the prof said this orally, or implied and always write such letters one can have reasonable doubts about his integrity And this is not a court anyway;

@WoJ Knowing what, if any, evidence exists will (hopefully) still lead to better answers.

@Anonymous yes I know, but OP gets the suspicions from somewhere, to the point of wondering if to take the prof as a reference. Sure, this can be paranoia but in any case I do not expect any hard evidence.

Maybe a better fit here?

@woj If there is no actual evidence, then the OP should add that to the question because that, too, will lead to better answers.

Options 2 and 3 are much bigger red flags than option 1. I would absolutely not take on a student who used a referee they didn’t trust and then argued with the reference they received, whether in writing or verbally, or spoke badly about their referee. But I do understand that there are situations in which it is reasonable not to use your MSc advisor as a referee.

There are conflicts between supervisee and supervisor and omission from the referee list might indicate that - or it might indicate a weak candidate that wants to include the most knowledgeable referee. I think all the options are not ideal. OP should get really strong references from the others to counter the effect of excluding the supervisor.

Kind of highlights a fundamental problem with academia. Moreso than in industry it seems weirdly common that people in academia end up in situations like this which are more about luck and inter personal skills than merit. Not that industry is fundamentally different, but the way people often seem to end up "trapped" with other people defining their career for them within academia seems... common . Why can't we live in a world where the answer would be a strong number 2, and it's distrusted at the first applicant making the claim, but once you have 10 applicants making the claim..  believable.

@DavidMulder I honestly think "being trapped" like this is much, much less common than Academia.se makes one believe. It's just that those that are are likely to ask a question about it. In reality, most supervisors (even the bad ones) write decent letters for their students, and students who had a conflict with their supervisors still find follow-up positions.

@DavidMulder And to answer the question: "Why can't we live in a world where the answer would be a strong number 2, and it's distrusted at the first applicant making the claim, but once you have 10 applicants making the claim.. believable." We live in that world. It's just that there are many groups and professors, so it's much, much more likely to be the first student who complains (to that person) about a specific supervisor than the tenth.

@xLeitix I do agree with you that academia.SE does make it sound worse, but at the same time, if I compare what I read on workspace.SE vs on academia.SE I would argue that the cases where there is no good option are FAR more common here. Regardless, agree with your first comment, but have to disagree with the second one, because the advice is that mentioning it at all is treated by Significance as a red flag. A red flag is a lot more than just "I won't necessarily believe you". The default is very often "say anything negative about anybody else and it only reflects badly on you, so stay quiet"

@DavidMulder I've written elsewhere about why academia and "the workplace" are so different in that respect, so I won't belabor it. But it's not "say anything negative about anybody else and it only reflects badly on you, so stay quiet," it's "on balance, I'm much more likely to trust a professor than an applicant, and so that plan won't work."

I doubt it's much different in "the workplace" where if your 40-year-old manager colleague said a 22-year-old wasn't a good worker, and that 22-y-o wrote in their cover letter how much a liar the manager was.

@DavidMulder about the 10 applicants thing, it's tough to happen for real, because the first 9 are basically sacrificing themselves.

@DavidMulder I’d rather live in a world where people weren’t so afraid of not choosing their advisor as a referee that they’d ask them for a reference even when they expect that reference to be negative. It is NOT compulsory to include your advisor as a referee, and strong candidates will have other academics who can speak well of them.

"...one of the people from our lab applied to several universities but was rejected by all of them because of his LoR..." is purely speculative. It is impossible to know this for certain. You might listen to rumours, but consider what @xLeitix wrote in the comment: "In reality, most supervisors (even the bad ones) write decent letters for their students". I strongly support this opinion.
For this reason, I actually recommend that you do ask your supervisor for a letter of recommendation. All other choices are suboptimal. Note, that if you apply to EU countries, mechanisms exist for you to see these letters.  For more details, see the discussion here, particularly the comment from @Marianne013.
I sincerely hope that you receive an excellent letter of recommendation and are accepted into the PhD program of your choice. However, if your application is unsuccessful and you have strong evidence to suggest that your supervisor included non-factual information in the recommendation letter, you may consider pursuing a defamation lawsuit. This could provide recourse if the rejection was indeed based on misinformation.

I totally agree that OP can't know why other candidates were rejected. But do we really want to go down a road where we ask an LOR of someone who we're so suspicious of we have to think about retaining a laywer?

Lies in a reference letter might be subject to a defamation suit, but why would the advisor fill a reference letter with lies? All they’d need to do to sink the candidate’s claims would be to give faint praise. Overemphasising real weaknesses would also not be subject to defamation action, and everyone has some. I agree with @JohnMadden — why use such a referee in the first place?

Do you have any other academics who you have worked with for your Masters? If so, you could consider asking one of those staff to give a letter of recommendation.
Also in my experience, universities will make allowances for the fact that your Masters supervisor doesn’t tend to know you that well - Masters degrees generally last for 9 months, and one applies for their PhD application after only 2 of these. Clearly this means that the Masters supervisor will not know you too well, and thus the undergraduate references may be weighted higher.


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Why are some mathematics papers seemingly so bad?
I am a PhD student in math beginning to do research. My advisor has given me a paper they want to generalize. It's pretty long with many dense, technical parts, and so, so many typos. The entire paper is about defining/exploring a space, but the definition of the space has obvious typos which make it unclear what the author means. Many definitions are similarly broken. Often the author states something is 'immediate from blah' where blah is a broken definition or a statement that is totally unrelated. I feel like most of my time reading is spent resolving these errors or unhelpful writing.
When I do resolve them and explain to my advisor, they they seem to agree that the paper is gibberish and that what I say sounds right. There is a lot of confusion neither of us can resolve. It's so bad that when I can't understand part of a proof, I start to wonder if it's just wrong.
This paper is not isolated -- the last couple papers I've read have been like this. It's not isolated to my field either -- my peers tell me similar stories about papers with typos that look like key smashing and more. It could be a lack of ability to understand on my part, but from all outside metrics I appear to be understanding what's in front of me. A professor even told a story once in class 'So and so proved this theorem. His PhD thesis was about how blah spaces can't exist, and his first paper was an example of a blah space.'
It's mind blowing to me that published papers/theses can be so broken and impenetrable, or even just false. I would be embarrassed to turn this kind of work in as a thesis. So my question is: how are these papers getting accepted? These are a few explanations I can think of.

Doing math is just really hard and explaining it is even harder, and most people who can do math don't put a high value on explaining it well.
No one is checking. Because there is a culture of bad writing and everyone is too busy, the peer review process just doesn't catch this stuff.
I am just a lowly grad student, still learning how to read papers, and eventually the process will be much smoother and faster so it won't really matter.

Edit: I think a more helpful question would have been this. What can I do as a student to make better progress through papers like this?

All 3 of your explanations are correct.  I should add that, when you know what the paper 'should' say, you frequently won't even notice the typos.  I should add that some subfields are better about than others.

Don’t surrender to The Dark Side. I believe that it is one’s duty to express oneself as clearly—not to mention correctly—as one can. I must report, though, that I spent an entire career amid scientists and engineers who were highly adept technically, but woefully under skilled in communicating technical content. Some were blissfully unaware, others downright scornful (“If they want to understand this, then let them do the work to get through it.”) And I’m sure that some were insecure about their work’s profundity and feared that clear presentation would expose some lightweightedness.

This might be nitpicking from me, but I would be happier if you added the word "some" to the title of your question. This from someone who has, just by nature of his age and experience, read an order of magnitude more mathematics papers than you ;-)

This is one of the reason why review process of mathematics papers takes much longer time compared to other fields. In some cases, review time can go upto 1.5 years or more. The reviewer needs enough time check those dense language and computations. Ofcourse, mathematics papers are difficult to study.

I don't think that the inference that all math papers are bad is empirically true. At least in numerical analysis and scientific computing (my field), poorly written papers are very rare. They generally wouldn't get through peer review.

Thanks for the edit :)

I find it strange that you mention typos several times. Sure, there are plenty of badly written math papers, but I've never had the experience that what made it difficult for me to understand a paper were typos. Generally the culprit is just bad exposition style and obscure terminology and notation.

There are indeed several reasons for which some papers can look bad and that this is a common feature of math papers but there are a lot of bias.

First, well or simply correctly written papers are unconsciously considered as normal and our brain recalls more easy remarkable things, with an emphasis on negative things.

Second, even in good papers, whatever it means, you will find things to reproach: too much or not enough details, too much references and not self-contained enough. I also happens to me when looking at papers I wrote ten years ago, to think "oh, this could have been made smoother" or "a transition between two corollaries would have been better".

It indeed happens sometimes that bad paper can be accepted. For the reason mentioned in the opening post, that is, that peer-review does not reject bad paper. Sometimes because the referees are busy. But also because, as pointed out by Alexander Woo, when you master well the topic, you read what should have been written and not what is written. This can also happen to a referee. The referees/editors also can be convinced that there is no fundamental flaw in the paper and "only" minor and easy to fix.  Moreover, the review delays can favor this phenomenon. It is not seldom to have two or three months to review a 40 pages paper. We can always ask for extensions, but the deadlines can put pressure.

A factor explaining why some papers can look like a first draft is the publication pressure. People have to publish, always more and always faster (I consider this as a cause, not an excuse). A consequence of that is that the proofreading and polish can be made in a rush.

I’ll augment my comment above about (what I hold to be) authors’ duty of correctness and clarity. A similar duty falls on referees. I’m not saying that their job includes copy editing; it does not. However, a proper review should indeed address not only the significance of a piece of work but also the quality of its presentation.


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Are there fully-funded Software Engineering Masters degrees in USA for UK students?
I am looking to get into software development. I have an offer for a Masters with a UK university but it an expensive course and the job market is much better in USA, paying much more generously. Hence, if it were affordable I think it might be a good idea to study there instead.
Would there be universities in the USA that are willing to provide significant funding for an international student looking to do a Masters in a course like software engineering? If it means anything, I did MSci Mathematics for my undergraduate and graduated as the top-performing student in the university.

You are very unlikely to find any software engineering Masters programs in the US that offer significant (or any, really) funding, regardless of nationality.
Software engineering Masters degrees are essentially professional degrees that provide entry into a lucrative job market, much like MBAs or law degrees. Accordingly, they come with the expectation that the student will pay their own way (possibly via loans), on the expectation that they will increase their future earnings enough to make up for the up-front expenditure of their education.


text:
What should I do after I found a coding mistake in my masters thesis?
I graduated 3 years ago and defendeded my master's thesis without any problem. Since recently, I am planning to go back to academia, so my former advisor and I are working together to publish my master's project.
While doing so, I've recognized coding mistakes that affect results statistics. Thankfully, it does not change the whole implication and main findings
but it changes some statistics numbers and minor results (which are not essential to the research hypothesis).
I don't know what to do. It was a mistake that I did not recognize at that time. I cried over and over for two days, and could not sleep soundly due to nightmares. I am panicking.
I've heard that I cannot make errata for my master thesis. (I don't know the reason why) What should I do?

People do mistakes. that's a general truth....And I am not talking specifically about your issue....

Good to find errors, which lead to improve

You've learned a valuable lesson that sometimes a bit of space from a project gives you fresh eyes upon your return . Rest well tonight knowing that you'll apply that lesson to your ongoing studies, and if it means  anything to hear it from a random internet stranger: you're ok!

Smile and wave

With all due respect, unless your masters thesis is something far beyond your average masters thesis... Nobody is ever going to read it. If you're really bothered, there's nothing stopping you putting up an errata section on your personal website and listing it under that.

If you really want to make an errata to correct your thesis and are being told you cannot, you should probably find out why you cannot - it may simply be that they don't consider it significant enough to add errata at this point, or it may be confidentiality issues.  Knowing that will help you know if you can self-publish corrections to the thesis in errata, or even just publish the thesis with corrected coding models.

Correct the code for the journal version, adjust whatever needs to be adjusted in the documentation, and move forward. Mistakes happen. My PhD thesis definitely contains at least one mistake (that I have found, and corrected in a subsequent publication). It's fine. As others have said, if you feel personally responsible, maintain an errata on your personal website for these kind of things.

Who did you hear "cannot make errata" from?  Where is this on a scale from rumor to official administrative policy?

@Technophile Master theses get submitted, graded, and that's it. They don't get published, so where should an erratum be put? The university website?

This is not unusual. It is good you detected it and now know more about the issue than you did before. The university has examined the thesis and decided you made sufficient achievements to receive your award. There is no need to go back and make changes to it.
If you have a personal research web page, or some other similar online media you could write blog about it that contains the update and errata. This way when people look at future publications they can read the errata, or you can cite it whenever you cite the thesis work.
The detection and documentation of the improvement shows your academic and research diligence and rigour.
How common is it: When I made my thesis only typewriters were available, so I decided to digitise it using OCR. I was shocked at the number of typos, grammar and spelling faults that were made. It was shameful! How we have progressed with our modern tooling!

In other words, the degree is a statement that OP is capable of conducting research, not a statement that whatever results the OP demonstrated is true

@AgnishomChattopadhyay, pretty much how it is with masters degree mills these days. I didn't think my mine was given that much a a run through as it was too much work for the examiners (I had extra time on my hands for reasons and really went to town on the rigor)

@AgnishomChattopadhyay I second that statement, as that's what theses are about, at least from what I was told. My own master's thesis was a good example, I set up a statistical model in order find a result - not only could I not find a result, but I realized whole model was flawed and effectively unusable in that state. Since I became aware of the issues quite late, I extended the discussion of my own approach and critically reflected all shortcomings, potential improvements, the whys etc. I ended up having a superb grade even though the result was "this approach is crap, please never use it"

@kopaka That result is a good result... And if the academic world didn't have such a bias against that boring result. (which to be fair is the most often result of scientific study. 301 different ways not to make a light bulb...) There world be a lot less papers with massaged data published.

@AgnishomChattopadhyay It seems OP's results were not 100% correct, but close enough to be useful.

The first thing you need to do is calm down. Deep breaths, go for a walk and appreciate nature.
Correct the errors, discuss them with your supervisor and make sure the published article based on the project is correct (perhaps add a note to the published article pointing out the mistakes in the earlier version in the thesis and explaining how they have now been fixed).
No-one will read your MSc thesis unless you have a personal website and you put it on there.

Congratulations on finding and fixing your errors.
Publish the correct numbers in the paper you are working on.
If you and your adviser agree, you can note that this paper is based on work you did in your Master's thesis, with updates and corrections.
In either case no one will ever look at your Master's thesis.

If you cannot create an erratum, this means that your master thesis is not properly published - or is only "lightly" published. This means that you are really only worried about having obtained your thesis by mistake. This is however not the case. Your evaluators will have looked at your capability to write a thesis and found you not wanting.
You talk to your former advisor after correcting the errors and after going through your code once again. Since your mistake(s) appear(s) not to be material to the outcome of the research, your plans for publication can go ahead.
You are certainly not the first researcher who published (even in your case, you did not really publish) results based on errors and you were lucky in that it did not affect the outcome of your research. Especially in CS, errors in published work are a thorny issue because so much is published in conferences that do not allow errata either.
Other than learning about your capability of making mistakes despite trying your best and being open to your former advisor and now collaborator, there is nothing you can do.

It sounds like the OP almost certainly has the right to publish their corrected thesis somewhere so there is something they can do. Just update the thesis and make it available (for example on arxiv or a personal website).

Master and PhD theses are meant to be your first contributions to the research community and everybody knows that these contributions are primary aiming for training young researchers. Nobody will judge you for mistakes like the ones described in the question.
Steps ahead:

Talk openly to your advisor about your bugs and how they affect the results.
As the publication is based on your thesis, you have to cite your thesis (otherwise it might be close to self-plaritism). The citation could be a sentence like "this paper is based on the first author's master thesis [Tube2020] but covers additional aspect, more polished results, and refined analysis." The last statement can be more explicit ("fixed minor issues in the analysis").
Enjoy your master thesis and your published paper!

@user253751 Sure, depends on what the mistake was and how it affected the results. I can image some mistakes are so severe that warning other peers justifies an article of its own.


text:
Making friends in academia and building connections
I started a new faculty position this past fall, which also entailed moving to a new city where I don't know anyone. When I first moved here, I was excited about getting to know my colleagues, as they were pretty friendly at my campus visit (pre-pandemic). But since my arrival, I haven't gotten to know anyone really. I have regular meetings with my department colleagues, but everything is so transactional. I know it's harder to have those organic, friendly chats on Zoom, and everyone was already exhausted from this pandemic when I first joined in the fall. But I'm really struggling with loneliness in this new work environment. I moved here alone, and am dealing with family health issues that have been emotionally draining (and some of my colleagues are aware of both of those facts). I've recently started seeing a therapist, so I'm trying to get the help I need, but more than anything I just really wish I had even one friend at work so every dept. meeting wouldn't have to feel like a meeting with strangers every single time.
I'm rather stuck, however, with what to do. I guess I expected that when I first joined, they would be the ones to welcome me and make an effort to get to know me a little (it's what I've done when I've had new colleagues). But now all this time has passed, and it's starting to feel like that window is closing. I don't know if I should just give up and accept that they're not social (or at least not with me), or make some attempts on my part. I've made some efforts here and there, but nothing has worked so far, and that has shaken my confidence, and makes me feel like maybe they don't care to know me.
I know that socializing and developing friendships at work might seem very secondary. This is an otherwise good job and I'm grateful to have been hired, but I just feel like such an outsider and very lonely because of it (I'm also the only one in my field at this university, so even the classes I teach don't even seem to fit in with my department's curriculum). I'm not about to quit my job over it or anything, but being in a perpetual state of outsider-ness is really getting to me and I don't know how to address it. It doesn't help that academia is often such an isolated work environment and many professors just aren't very social even in the best of times (hence why I'm posting here specifically).
EDIT: Just wanted to comment here that I'm very grateful for all of the responses. I feel a little less freak-ish, and a bit more motivated to stay patient and keep the efforts going in the meantime.
I'll also add that I think one of the reasons I feel so bothered by my department's current dynamic is that it makes me feel like I need to conform and be as transactional and subdued as the rest of them, which is very contrary to my own personality. Anyway, I think that trying to connect with people - but not at all on my own terms - is contributing to the stress of it all, so I'm glad to have had that realization too.
Thanks so much for the advice and words of encouragement!

I added the COVID-19 tag. You might want to edit your question to emphasize this aspect more, since this question will lead to a very different answer in the present time than in a (hopefully near) future in which the pandemic is over.

I just want to explicitly say that what your experiencing is completely understandable given the situation, and I'm sure there are so many people with very similar feelings. Not that this makes everything better for you, but at least I want you to know that there's nothing wrong with you! These are terribly challenging times, and meeting new people in a new place is difficult even under ideal circumstances. Good for you for reaching out in various ways to take care of yourself as best you can!

When the pandemic is over, suggest organizing some weekly mixers/social hours (maybe including grad students, maybe not) in your department or such. With snacks/drinks/etc. Grad students often like these, and profs might appreciate it too, given the previous social distancing.

I don't know if this is much of an answer, but it's become more than will fit in a comment.
If you just joined in Fall 2020, it's not unusual that you haven't made the kind of connections you're looking for yet, especially given the challenges of the pandemic. I'm a PhD student, and I'm sure it's very different for faculty than for students, but I'm not fresh out of undergrad and have been through a couple career transitions prior to grad school. In my experience it takes a year minimum—even in the best of conditions—to organically develop relationships with coworkers/colleagues. (It took me longer than that to build close friendships with folks in my cohort, and we had weekly, in-person classes together for a year.) Genuine connections with coworkers tend to accrue in small increments over that time, and almost always in the interstices between "official" work demands. It sounds like you're fully aware of all this, but an occasional reminder doesn't hurt.
As you mention, everyone is exhausted these days. Perhaps your colleagues are all on the introverted side, but it doesn't sound like this situation has much to do with their feelings about you specifically. If they'd all been actively avoiding you or unfriendly, that would be a different story (and this is not the story you imply, at least, when you say your efforts "haven't worked so far"). Your colleagues may also be trying to give you space to address (or not feel close enough to engage with you about) your family health issues.
In any case, the window is far from closed. I'm still friends, a decade later, with some former colleagues who barely even spoke to me for the first few years at my previous workplace. And although I'm obviously not a super outgoing make-friends-easily type of person, my sense is that that sort of experience isn't unusual.

Ah mate, I am in the same situation. Moved city to a new place, a new job in Feb 2020. What a time to do so!
My colleagues are super nice, but covid just makes everything hard. People are having personal issues, burnout etc, and it makes the friendly "hey let’s get a coffee together" very hard (legally impossible often). Not just logistically, but also psychologically. Mental health conditions are skyrocketing, the worst since WWII in the UK, and of course this has an impact on the ability of everyone to socialize.
People are tired, "Zoom burnout" is a real thing, and many people are just exhausted of all this screen time socializing, all the time. Zoom does not substitute face to face interactions, you can’t talk 4 people at the same time, argue, or tell a joke. All does feel like "mandatory fun" when you are having a friendly chat, even when it’s with actual friends.
But remember: This is the pandemic. It’s not you, it’s not them, it’s the very rare and extreme situation we are all living in. It does not feel like an extreme situation because our daily lives are very mundane, but it is very hard for the human brain, especially if you are a social person.
I am sure many of those people will be more than willing to go get a coffee/beer/social_thing with you when it’s possible.
I am telling all this from personal experience, not only with how my colleges behave, but how I personally behave. I am a super social guy, I love meeting people and I think group relationships are key in academia and research. Not only that, but some of my best friends are people I met on the job. But I am tired. I often don't join the "social coffee" chats our group organizes, I don't try to catch up with people to see how they are. Now, believe me, the moment all this goes out, I will be the first to propose a night in the pub! Your window is not closing, people are just doing the best they can to survive this thing.

I also started a new faculty position during the pandemic, so I know how you feel. There is also not really anyone else at my university working in a similar area. It's very difficult to develop new relationships with colleagues via Zoom, etc. While it isn't a substitute for the casual encounters which help build connections with new colleagues, there are a few things I have done to at least try to get through until in-person social contact is possible again.

Press forward with existing collaborations. This has the benefit of progressing my research, but also keeps me in touch with friends and colleagues around the world socially.
Reach out to connections about starting new projects. Similar to 1 there is also a social side to this.
Organise Zoom 'coffee' meetings with other faculty members (one-on-one or as a group). In particular other faculty at a similar career stage. Many people feel the same way as you, sometimes all it takes is someone to break the ice.
Get involved in non-university social activities. Depending on the pandemic situation where you are some in-person activities may be possible (for example outdoor team sports are allowed where I am). In my opinion this is a good idea even in non-pandemic times in order to have an escape from work.

Hopefully we will all be out of this soon!

There are already many good answers specific to the academic environment. I just thought I'd add my two cents as an expat.
I moved to a different country 8 years ago and struggled much with the same issues you describe, though I had the advantage of being a student at the time and not having a global pandemic going on. Coincidentally, this country is rated as one of the hardest places to make friends in, I found out later. My problem was people were friendly but it was difficult to make a genuine connection because most people were local and already had all the friends they needed. Yes, it sounds silly. Yes, it was completely true. The friend saturation curve is real and the older you get the more likely the people you meet are already at their desired maximum friend capacity. I know you just moved to a different city instead of out of country, but I think the same situation applies.
The solution I've found: Find the other foreigners/non-locals.
Those people are also lonely and they'd love to be friends with you! You just need to find them. If the city is large enough there are bound to be facebook/social network groups for folk new in town, whether they be from abroad or not. Your university might have some sort of international office. You could try to start a zoom coffee club/ Friday beer at your work place or find out if there is one. Or join some interest group, sports club ect. It's good to be friendly at work but there is no need to limit your social contacts to the work environment.

Loneliness for new faculty is definitely a problem, even in non-pandemic times. Students/Postdocs/reserach fellows often have research groups or cohorts that provide a ready made professional circle that isn't present when you start as a new faculty. To make matters worse, you will often have had to move a new city/country.
Are there other new PIs at your place? Perhaps you could reach out to them? I'd start by approaching them individually for a Zoom coffee.  Perhaps not even in your department, but in related ones. You don't need an excuse beyond "lets get to know each other and each other's work". We have a group of young PIs here that have been key to my development - people who've join the dept in the last 10 years. Mostly we drink together, but also we science together occasionally even now (via zoom).
You say that you feel a bit out on a limb in your dept. How about creating a trans-campus seminar series or journal club or discussion group on some topic connected to your work? Or a group especially for new faculty in any department of the institution.
Finally there are dedicated online communities for new faculty. New PI slack is an online community for new PIs, open to any new faculty member anywhere in the world, but I think the members are heavily enriched for North American and Biomedical science. There is also NewPI_UK that is UK focused more on the UK academic system where people worry about different things (e.g. there is no tenure in the UK, our grant system is much more project focused rather than program focused etc). I suspect there are others.

+1 for New PI Slack. It is both US and BioMed focused, but a lot of the issues you'll face (hiring, teaching) are similar. I've found it incredibly useful.

There are two aspects to "making connections": professional and personal.
First, a few words about professional connections. If you are the only person in your subfield at this place then most of your connections are normally found elsewhere, say through conferences and such. But you can also develop a side interest in a related field that is more widely represented at your place. One with an ongoing seminar series might be best.
But the focus here is on personal, local, contacts. Assuming that you don't want to work all the time, which is unhealthy in any case, look for some activities and interests that you share with others, even with grad students in a large place. When I was a doctoral student at a large university, a few of us were very interested in cycling, normally 50 miles or so a couple of times a week. Most of the group were young faculty. The fact that it was aerobic was an additional point in its favor as there is nothing better to clear the mind than a good workout (yes, debatable). Some of us played paddleball/racketball/handball occasionally. I usually lost. Some of this may not be possible in pandemic times. But running/jogging in a widely separated group should be safe enough and is healthy.
You can even walk and talk with proper separation. The talk could be professional or not. Commiserate with your peers about how badly your favorite sports team is doing.
The grad students, along with spouses, organized a pickup softball game once a week. Again, faculty were welcome.
But there may be opportunities for museums or music, especially if we emerge from the pandemic. Book discussion clubs. Interdepartmental things might be possible. Look for common interests. Or even spend a bit of effort to expand your own interests.

In our company we have started to create "coffee break" video sessions which are explicitly not about work. Most are once or twice a week; and span different organizational boundaries (e.g., mostly on the team level, sometimes more orthogonal to that).
Maybe you can encourage such a voluntary coffee break in your group as well. I would specifically not make it something outside the regular times of work, but smack in the middle. Think of it like the time when you accidentally meet people at the coffee machine. Use the time to talk about anything you would do to socialize.
Also, if you have a common text chat infrastructure, just use that to actively do private or group chats with whoever you can think of. I.e., if you have the feeling that someone mentions something that bothers them in one of your meetings, just follow up on that ("I noticed ... are you OK?"). You don't want to be creepy, but maybe something develops from that.

Whereas I agree with the answer of cpit, I do think that we have lost the culture of welcoming new members to our working groups.
This might have different reasons.
At first, science and academia tend to build an environment, in which everybody is under pressure to produce some results. And in general, this is not an easy task. Also, it is easy to identify ourselves with the outcoming and the progress of our work, as we usually work a major amount of time on our own to gain those reuslts. I know it from myself: When things do not work out that well in my research I tend to focus a lot on it and I may also become rather unsocial.
Nevertheless, I think this is neither good nor normal. We all should feel responsible to give newcomers a warm welcome. Even if (or maybe especially because) our experience was different when we came to the insitute, university, etc.
My experience is that two crucial points correspond to the achievement of a successful integration process.
1.) The team leader: He or she has to form a team, where everyone feels respected and well esteemed. If this is met, I have no problems to welcome other people - as there is nothing that I can lose from somebody entering new in our group.
2.) The institution has to set up an environment, where it is simple for people to meet, that didn't know each other before.
I noticed that at universities the rôles are sometimes not well organized. The administration of the university might be one reason, why you are here, but they live (obviously) in a completely different world.
The professor might be another reason why you are here, but he or she is busy and trusts the students, that they will welcome you.
Whereas the students either are locals and then often do not have the motivation or the means to integrate people from elsewhere (as they never made a similar experience or they have reached a saturation level of friendships as pointed out by Henya). Or they are not locals and may experience the same issues like you.
Both of the points above cannot really be changed by you.
But what you can change is the way how you treat this situation. There are many other people facing the problem as you, and this is a good starting point (as many other posts already made a lot of suggestions here).
And giving other new members in your group later on a warm welcome might be an even better one.


text:
Another undergrad or a masters degree before PhD?
I have a low GPA (2.97) and by the time I graduate this coming Summer I'll have roughly >3.01.
I'm debating whether I should add another major and not graduate in Summer or graduate in Summer and get a masters. The assumption is that I will get a 4.0 in either the added major or the masters.
What is the better choice/what looks more attractive or makes up for my GPA more? My only scar on my CV is my GPA as I excel everywhere else.
Background:

I study computer science and the masters or other undergrad major would be mathematics.
I do research in artificial intelligence and would be focusing on cog sci programs for my PhD.
I want to get into a top school for my PhD.

For clarity:

I'd be adding on a major and would eventually graduate with both CS and math.
My PI has said he'd pay for my remaining undergrad provided I stay in the lab (which is a good thing; he's a top AI researcher at my uni)

Update: I've decided that I'm adding a math major and going to attempt to get a 4.0 for the remaining time here while continuing research.

I guess this would be better if you ask your advisor this question.

I have and it's a different answer depending on which adviser you speak with. My PI also has differing opinions as well. This question is mainly to get more opinions.

In that case, this question may end up being closed as primarily opinion-based...

@NatalieHogg I may be using opinion lightly when describing what I'm looking for with this question. Though, opinions will be a large portion of the reasoning behind answers to this question, those opinions are not solely based on personal preference - but hopefully more experience and knowledge of academic politics - and thus I don't think this question should be closed as it may serve as a general help for others in a situation similar to mine. If it is closed, though I'll repost it with wiser wording.

Assuming you get another major and assuming you get a 4.0, what will that bring your GPA up to?  Unfortunately, even with a 4.0 Masters, an undergrad GPA of 3.01 is going to be difficult to explain.  Top schools are going to filter applicants out using roughly a 3.5 GPA cutoff.

@Hobbes It would bring it up to roughly a 3.2-3.3. I also am a researcher and will have publications by then, have hopefully attended REUs, and already have corresponded with some profs at top schools. I believe if I keep up the political games I'll be able to get passed their hard cutoffs and have my apps considered in full. The only issue is my GPA. So, I am curious as to which option - masters or another major - proves most that my GPA is not my aptitude but merely me being confused and emotionally distraught (which is true).

3.2 - 3.3 with strong research and recommendations will be more competitive.  I think this would be better than getting an MS if you are sure you want to pursue the PhD.  Even with a 4.0 in a MS, that undergrad GPA may come back to bite you.  Hard to say.  Which option is cheaper?

To switch from CS to math, you have to show you have enough math courses.  You didn't talk about that.
Poor grades in the first two years don't matter very much.
Your grades in your math classes and your more theoretical CS classes will carry more weight than, say, a class in operating systems or a very coding-intensive class.
You might need to pick out the key classes you think support your application the most strongly, and put them in a table, showing the course title, brief description if the title is not self-explanatory, and the grade.
Financial considerations could be important.  If you would have to go into debt to finance further studies, then you might want to get a master's in CS, with a TA-ship, but load yourself up with math and math-oriented courses as part of the master's.
It's not clear to me where you would do the master's.  Are you thinking about doing it in the same university where you're doing the Bachelor's?  If not, moving to a new school brings a lot of unknowns.  On the other hand, if your current university is not a great fit for you, for whatever reason, then it could be beneficial to go elsewhere for a master's.
One difference between taking extra classes as an undergrad and doing a master's is that if you take a 500 level class where both seniors and first-year grad students are enrolled, expectations will be higher for the grad students.  AND note that as a grad student you would be expected to earn an A or A- (or a B in the worst case).
Note that if you want to take more math classes at your current institution, there are two additional options that you have not mentioned:
- just wait to graduate, and take some more classes
- go ahead and graduate, and then take some more classes as a non-matriculated student
If I were going to evaluate your admission application (that is a big if -- I have never sat on an admissions committee), I would want to see that after three years of college studies, you started to take things more seriously, you started to do very well, and you started to take more responsibility and initiative.
Taking the initiative means finding math classes that help you mature as a mathematician.
So, bottom line: I think you should expend your energy choosing classes wisely.  I think that matters more than exactly what your status is when you take those classes.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


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How do I acknowledge an equipment malfunction in a manuscript I'm submitting to a journal?
After a four year break, I'm finally getting around to submitting my MSc. research to a journal. My research involved time series data - analyzing a food sample over a series of days using a number of methods. For one of the methods, HPLC, the equipment was malfunctioning on the first sampling date, so I only have results from the following two sampling dates. I realized this significantly impacts my work, but I do have a statistical difference in between the two dates that the equipment was working, as well as 15 other attributes that were successfully analyzed on every sampling dates and tons of other takeaways. Any advice on how I can professionally say "the damn equipment didn't work and I was a lone grad student in the lab on fall break" without throwing out the HPLC data that I did collect?

"I realized this significantly impacts my work, but I do have a statistical difference" - Not related to your question asked, but be careful with this type of thinking, as it results in publication bias and negatively impacts scientific progress across the whole literature. Your research results have value whether or not a test for statistical significance finds sufficient grounds to reject the null hypothesis. If people only report significant results, then the literature will be saturated with false positives without contrary evidence.

Maybe:
"The first data point was lost due to a malfunction of the equipment."
"Due to problems with the instrumentation, we could only obtain two HPLC values."
You might need to give an explanation why the experiment could not be completed or why the data is not necessary.
Something a bit stronger than "The HPLC values obtained conform to the general tendency."

Data was not lost. Data were recorded or attempted to be recorded. For the experimental reporting it's best to spell these things out rather than paraphrasing.

This approach just raises the questions of why we should believe any of the HPLC results: so if it was broken on day one, maybe on days 2 and 3 it just spat out random numbers which just happened to match expectations based on the other techniques? OP needs to demonstrate (to themselves, at least) that the kit was working and the output is worth bothering with in the paper...

That is not the question that was asked. I assume that posters are ethical. That implies that it was a clear, diagnosable, and diagnosed malfunction.  OP cannot repeat the experiments because OP has been out of the lab for four years.

the damn equipment didn't work

... which is nothing particularly unusual. You mention it and that's it.
You may want to spell out that & why your samples could not be stored without degradation or were used up by the HPLC, which later on was found to be unreliable. Or whatever actually happened.

and I was a lone grad student in the lab on fall break

My professor would have said: that may be a practical reason, but it is not a scientific one. I.e., this isn't anything that goes into the paper
A more precise formulation of this catchy quote would maybe be: this is a practical (lab organization) reason that however isn't needed here, because it doesn't add anything of scientific relevance over the more direct (also practical) reason of "detector not working" - and the scientific impact, i.e. that the loss of data needs to be taken into account by limiting the conclusions, isn't changed.
The milk is spilt, and that's it for the paper. For the paper, the only remaining question is whether it still has sufficient content without these data, and whether you can justify not doing an additional run of the experiment (you may want to discuss this).
For your professional experience, it will be good to consider planning experiments in a more fault-tolerant manner in future.
E.g., to plan experiments in a way that does not hamper finding help if needed. Or adapting the analytical method to retain aliquots (if proper storage is possible) in case something goes wrong, planning more samples from the beginning so the results of a few missing chromatograms are not devastating. Or to be more redundant in your measurement planning in general.

 without throwing out the HPLC data that I did collect?

You only throw away the unreliable (or non-existing) part of the data. That may make the data analysis more complex, but in general it is no excuse to exclude the remaining perfectly fine measurements.
Typically the way to go in the paper is to include what you have, and limit your conclusions accordingly if some data is missing.
If the other measurements provide sufficient information, the paper is still fine.
If the loss of one (set of) chromatograms means there's not sufficient information left, that is not really different from not having obtained sufficient information for any other reason, including bad planning of what analyses are needed.

update wrt. @Snijderfrey's comment:
(I'm analytical chemist, though specialized on spectroscopy rather than chromatography; have working experience also on food samples, and have collaborated with food chemists)
And yes, science is to some extent subject to practial considerations. So a more precise distinction (and less black/white than the catchy quote) would be is the scientific impact of the practical decision justifiable?
The loss of a complete day of chromatograms out of 3 days in total is an order of magnitude where as a reviewer I'd like to see some explanation.
Part of this is that there are (bad) scientific reasons that could have lead to the outcome, e.g. "we never thought of HPLC until the first experiments were over" - which would have me think what else they did not think about...
The practical reasons @Snijderfrey lists are justifiable to me as they fall in the category of things that inevitably happen - though one can and should work towards low probability (as in: working efficiently):

Lab equipment breaking down:  detector lamp do burn out, capillaries or fibers or cuvettes break, columns go bad, you name it. (wet-lab work unfortunately doesn't have a Crtl-Z key, and in particular not if it's destructive analysis like HPLC)
Again the line is not sharp between the need to replace consumables, regular maintenance, and repairs.
In OP's case, it seems that the proper person not being on holiday
may have saved the day's experiment. Still, of all possibilities how
such instruments can and do break, only a fraction can be
repaired in short time. Or the alignment and/or calibration after the repair takes so long that the sample is anyways degraded.
Yes, it is possible to guard against this failure mode, but it is maybe (likely) not worth while for OP's lab. (As opposed to e.g. a clinical lab that may have a policy that people have to plan their holidays so that certain skills are always available - because the consequence is patient safety rather than some bothersome explanations in the paper)

a sample being spilt/preparation error.
This often doesn't lead to 1/3 of the data being lost: one may be able to take an additional one, or only one replicate/aliquot/portion is lost (this failure mode is one of the reasons why we do replicates).

Science operates at the boundaries of the known. We deliberately do experiments where boundary conditions dictate work flows that are not optimal from some point of view but that are still justifiable or necessary trade-offs: I've had samples where portioning had to be suboptimal because we could not grind (seeds that were potentially to be sown later on).
I've also had far too few patients in a data set to really draw
conclusions - but they were all we could get during 8 years of
collecting - which we considered justifiable. Whereas I've also had too few patients in a data set
where more should have been much easier to collect, and that IMHO
amounted to bad science...

The flexibility to adapt analysis to slightly unbalanced data and limiting conclusions is to me just another tool to adapt to the risk of things going wrong - like planning replicates in advance so the loss of some data doesn't endanger the whole study/paper.

BTW: unless you have concentration data from other methods (with better time resolution), you may have significant difference between days 2 + 3, but you don't know whether that's day-to-day variation, field sampling error (unless you can rule that out since you took a sufficient number replicate samples each day), or time-dependent change of the original specimen.
BUT: this is no very substantial change whether you have day 1 or not - also with day 1 it would be extremely unlikely that you could separate these sources of variance.

Good answer, one remark to "that may be a practical reason, but it is not a scientific one": Isn't that also true if there is a malfunction of the HPLC device, mistake during sample preparation, or similar? Who cares for such reasons if a data point is missing? Including such an explanation into the paper inevitably results in a bigger chance of unfavorable reviews. The key point for me is "include what you have, and limit your conclusions accordingly if some data is missing".

@Snijderfrey By giving the reason of one missing HPLC set, it looks less like you are suppressing data that does not match your hypothesis. And sure, the malfunction could be made up, but it still leaves a better impression and proactively hints the reader to a potential weakness of the data set.

@usr1234567, I agree that it is a good idea to "proactively" make the missing data points known to the reader. This can be easily achieved by properly describing and discussing the data on a scientific level. There is no need to say anything about equipment not working. You can do it, of course, but it does not bring you any closer to draw conclusions about your hypothesis.

@Snijderfrey: you're right, this is also practical - I'll clarify my answer.

There may be field-specific "cultural differences" here. To me, describing how the data were lost is properly discussing the data on a scientific level. I was once in a cross-disciplinary workshop with physicists and one interesting outcome was that the level of detail considered appropriate in a publiation differed: we chemists thought of the physics papers that they didn't give sufficient experimental details, and the physicists said of the chemistry papers that they'd be afraid to be scooped revealing so many details.

The question you need to settle first, is why you believe that your HPLC data from days 2 & 3 is meaningful. "the damn equipment didn't work and I was a lone grad student in the lab on fall break" doesn't come across as though you understand what the problem was, and so how can we trust that you can then be certain that on days 2 and 3 you got meaningful data? If you're not sure, throw the data out.
If, and only if, you are sure that the data is actually valid, then a trivial formulation would be "We analysed the data using techniques A, B, and C, and on days 2 and 3 we were also able to use HPLC to..."
Whether the HPLC kit was unavailable on Day 1 because it was broken or because someone else was using it isn't the readers' business. That the HPLC data presented is meaningful, very definitely is.

It could be as simple as the recorder did not record, the laptop crashed prior to having the data saved, or OP forgetting to plug in HPLC device the first day.

@usr1234567: I doubt that - I'd be surprised by OP being allowed to operate an HPLC on their own without having sufficient proficiency and experience with the instrument to operate it well under usual circumstances. Not recording or computer crash would typically mean the loss of one run/replicate, not a whole day's data. Not being plugged in is obvious and would mean that OP noticed that before the first aliquot is used up.

@LouKnee: There is no risk of the HPLC producing "random numbers" and OP not realizing that. Plus: HPLC typcially requires that you run calibration samples  - and for sure you need to do that after repairs. There are certainly more subtle ways things can go wrong (also in HPLC), but I don't see any reason to mistrust OP's day 2 + 3 data more than usual for published HPLC data.

@cbeleites unhappy with SX That's not really my point: it's for the OP to know how reliable the day 2 & 3 data are, but they probably don't actually have to justify missing day 1 at all (unless they pre-registered the protocol or something like that).

How about something simple like

Despite having problems with occasionally malfunctioning equipment, we were able to obtain valid results except for one set.

I'm not sure I've captured exactly what happened, but something simple like that. Add the name of the manufacturer if you must, or give them an acknowledgment elsewhere in the document. It might be best to separate the two, putting the ack in a footnote or acknowledgement section.
You can, of course, strengthen the wording if you like (...serious problems...), but don't rant in a scientific paper.

I would avoid the word "tinker" since it can suggest making changes without understanding of the problem. In British English the word also describes a mischievous child.

This is too indirect.

@user2705196, OTOH, it is a mistake to vent rage in a scientific paper. It isn't a social media post.

Despite having to tinker with occasionally malfunctioning equipment is the standard modus operandi for experimental science. Worse, what Rob says: "tinker" implies limited understanding of the equipment.

@LouKnee, better now?

Not really :( ... if the equipment can't be relied on then you can't trust the results, and part of the experimentalist's skill set is understanding the kit to the extent that you know when it's working properly, and when it isn't and why. If you don't know it's working properly then it's spouting garbage...

NB > don't rant in a scientific paper. is very definitely true!

What does malfunction mean? Did the user something wrong or is the apparatus not reliable? If it is the latter, is the apparatus in a bad shape or in general flawed? Leave out the manufacturer, it looks like a cheap scapegoat. It is your responsible to use a flawless setup!

@usr1234567: name of manufacturer anyways (always) goes into the materials & methods section in (analytical or food) chemistry. Regardless of how well the equipment did work.


text:
Publication during my intermediate work
I work on wireless communication topic for my thesis and want to published some my intermediate work on my thesis.
There are conferences, Workshops, posters, magazines (did I miss something?). All of them has a deadline for paper submission, which are 2-6 months yearly then the conference/workshop itself.
I search the list of conferences in 2023 on ieee website, but most of deadline were passed for submission in this year. Did I search wrong way? Should I search somewhere else?
Could you share your experience how you search conferences for publishing your work? Some advices how to write researches paper which were useful for you?
Thank you in advance!

Both IEEE and ACM have multiple conferences each year and many are held annually. If you are a member of either or both organizations they typically email announcements of upcoming conference deadlines (call for papers).
Their publications, such as Communications of the ACM, also give notice of upcoming conference deadlines. If you aren't a member then you can probably find these publications in any university library.
Note that "Student Membership" is typically available at a lower fee than is paid by professors.
The organizations also have SIGs (Special Interest Groups) that focus on a particular area. Membership in a SIG will bring you email of upcoming events, including conference deadlines.


text:
Is there a way to cite two articles which share some authors in a single sentence?
I want to cite a pair of articles using in-text citations and they share some of the authors between them.
Does there exist any acceptable way to do this by joining them in a single sentence?

A MWE would have the following articles:
[1] Tom, Dick, and Harry. (2021). Generic Article Name. Journal 1.
[2] Tom and Harry. (2022). Another Generic Article. Journal 2.
And if the authors did not overlap, I would write something like:
"As the results of Tom, Dick, and Harry [1], which are corroborated by the study by Tom and Harry [2], show..."
Ideally, I would like to shorten this to something more like:
"As the results of Tom and Harry [2], as well as their prior work with Dick [1], show..."
Is it acceptable to abbreviate citations like this or some other way? Or should I go with the longer version?

Since you're using numerical citations, do you really want/need to write the authors' names too?

Not really, but that's how I have been doing it. Do you suggest dropping either? I feel like they make the text clearer than if I just used the number, but that's just my opinion.

It depends on where you want to publish. This is a question of style. Generally such questions have as part of the answer "check the local style." Find out what they want in the place you hope to publish, whether a journal or an academic committee or whatever.

I don't see anything wrong with either of your two examples, whether the names are overlapping or not. I say this with the caveat that every field and journal has its own particular style and conventions. My experience is primarily in linguistics, which seems to have a bit more intra-discipline variation and flexibility than some other fields.
If you think it sounds awkward, you could simply rewrite the sentence to avoid the names, e.g. something like:
"As shown in prior work [1,2]"

Thank you! I was unsure of how to write it, but it's reassuring that you don't find my examples too outlandish. I like your example too, since it's very concise, I may use it as well.


text:
Algorithm plagarism?
Say I watch some YouTube videos to learn merge sort, and during the lesson the code for merge sort is shown and explained, if after this I write my own program and use the merge-sort algorithm I learned from the video, am I plagiarizing?
Say if I need to hand in an project for university and it requires a mergesort on an array of integers in a part of the program like the example in the lesson was, can I get wrecked for plagiarism if I used the mergesort method from the lesson to use in my project?
edit: assuming that I completely understand the algorithm and can explain every part

Do you plan on citing the video in your submission?

I was just making up a situation, I'm just wondering if using algorithms the exact way I learned them off the material counts as copying, be it from some website, video, or textbook.

Best to ask your instructor for what is allowed. At the very least, if instructor's are OK with students getting inspiration from various online resources, then citing the source(s) is a excellent safeguard against plagiarism.

If you copy the code without citation, that would be plagiarism. Using the ideas from that video but writing your own implementation of the ideas would, in my opinion, be OK because mergesort is such basic knowledge (in computer science) that citations are not needed (rather like using the Pythagorean Theorem or the chain rule for derivatives in mathematics).

Plagiarism is using the words or ideas of another without proper credit.  So, if you don't give credit, you're plagiarizing.  If you do give credit, you're not.  It is really that simple.
In your particular case, there may be something else at work.  If your professor taught merge sort, and the assignment is to demonstrate that you know how to do it, then you might be in trouble for copying another's code even if you give proper credit; it's not plagiarism, but it still might not be allowed.   As Mad Jack has said in the comments, ask your professor.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/3.0/


text:
Is it plagiarism to adopt specific questions from a pre-existing questionnaire?
I’m currently required to make a questionnaire for my research. Is it okay to use only specific questions from previously published questionnaires as these questions perfectly apply to my research context? Will that be considered a plagiarism if I cited these questions?

Aside from the plagiarism issue, be careful that questions removed from a larger instrument may not have the same properties as the whole instrument. Any validation of the original set does not apply to the questions you pull out selectively.

Ii sounds like you're quite inexperienced with doing research. I recommend you have an extensive discussion with your supervisor about what constitutes plagiarism.

As said, if clear it wouldn't be plagiarism, but it could be bad science. Perhaps science such bad that it would be an unethical waste of your participants' time.

Plagiarism is not copying. Plagiarism is copying without attribution. By definition, you can not commit plagiarism if you cite the original source and make sure the reader understands well that which parts are others, and not yours.

you can not commit plagiarism if you cite the original source - Not true.

@Kimball The main goal of the webpage we are at is educational and to help the asker. Your comment doesn't really do that much as it stands now. Care to elaborate? Is it my particular wording that you don't like, or is it the standard definition of plagiarism you disagree with?

E.g., copying text and merely including a reference to your source without proper quotation can be plagiarism.  I also wouldn't say your definition is standard.  See https://en.wikipedia.org/wiki/Plagiarism

@Kimball I see your point, I assumed "attribution" covered that in my answer. I will edit for clarification.

I don't see this as plagiarism. Plagiarism is passing something off as your own words (or thoughts perhaps) without attribution. If you publish an article under your name as author which contains unattributed text copied from elsewhere, that is plagiarism. But here you are using a questionnaire as a tool to collect information. You are not claiming you wrote those questions nor would it be reasonable for someone to assume that. In fact, it would be unexpected and bizarre to cite sources for the questions in a questionnaire. Things could be different if you make other use of the questionnaire. For example, if you publish it as an appendix to an article you probably should include some attribution to sources.

"Is it okay to use only specific questions from previously published questionnaires as these questions perfectly apply to my research context?"
Ans: Using specific questions from previously published questionnaires may be acceptable if they are relevant and appropriate for your research context and objectives. However, you should not rely solely on existing questions (to cherrypick) as they may limit the scope and depth of your inquiry. Instead, you should design your own questionnaire based on a thorough literature review and a clear research gap. This will ensure that your questionnaire is novel, robust, and tailored to your specific case.
Will that be considered a plagiarism if I cited these questions?
Ans: Questions should only be cited if they are relevant to the same context. In research questions, context is crucial. Different fields of research may pose similar or identical questions but with different meanings and implications. For instance: “Did the proposed model improve the performance?” This question could appear in both an Economics paper and a Software Engineering paper. However, these papers should not cite each other’s questions, as it is too common of a question and belongs to different contexts.
If the context is partially overlapping, it is advisable to address this issue of question repetition in the Related Works section, where the differences in context for the same questions can be further discussed and clarified.
An example can illustrate this point: suppose I am proposing model X in my paper P for a certain task. The current state-of-the-art (SOTA) approach, model Y, was proposed in the paper P’ for the same task. I want to include the following question in the questionnaire for the user study of my paper: “On a scale of 0 to 10 (0 being completely disagreed and 10 being completely agreed), do you think the proposed model performs better with respect to the SOTA approach?”. I have already explained the ‘proposed model’ and ‘SOTA approach’ (model Y) to the user group. However, when I examine paper P’, I find the exact same question (verbatim) used by the authors of P’ to validate the superiority of their model Y. I need to use the same question for my model X to demonstrate its superiority over model Y. Therefore, I acknowledge this issue in the Related Section, where I cite paper P’ and explain that I have followed their work and asked similar questions in my user study for the same purpose.

This doesn’t answer the question.

modified the answer

I'm still not sure it does. As a psychologist, I interpreted the question about questionnaires differently, although I'm sure your interpretation makes sense in a different research context. However, it's still not clear what the answer to the "is it plagiarism" question is

@AzorAhai-him- The problem is that copyright infringement is always wrong, but plagiarism is mostly wrong in academia only. So in academia, it's discussed a lot more. To the point where people completely forget about the much more common case of copyright infringement.

@gnasher729 Copyright infringement is a law, not a moral guideline, so it's not necessarily "always wrong." That said, using a published questionnaire is not copyright infringement, because they are published for use ... also Mashuk did not mention copyright infringement so I'm confused by your comment in the first place.

First, you need to understand the difference between plagiarism and copyright infringement. If you cite your source, it's not plagiarism, but if you copy the questionaire without permission, then it is copyright infringement.
Second, the questions in a questionaire are rarely random. Very often a questionaire contains questions where the interviewer has no interest in the answer whatsoever, but these questions are added so the interviewee cannot figure out what the interviewer wants and cannot give the answers that they think the interviewer wants to hear. So if you remove these "pointless" questions, then the answers to the other questions can and will change.

Interestingly, a journal recently withdrew a paper that used a questionnaire copied  without copyright licensing
from the author.  https://retractionwatch.com/2023/06/07/journal-pulls-paper-from-ethiopia-for-unlicensed-use-of-questionnaire/


text:
How to validate scientific ideas outside academia?
Long story short, I have some ideas regarding the field of psychology and I am looking into ways to validate them with people with experience.
Options I see:

Submit a paper and wait feedback from a journal. I understand the hurdles that come with this option. I'm wondering if this is totally unrealistic for non statistics based psychology.
Contact people in academia. I'm not sure if anyone would even listen. Moreover, I am
not very familiar with the jargon and I can't quite communicate my
ideas in a casual conversation.
Write a book. This is definitely a non-scientific approach but may be more feasible considering how revolutionary Eric Ries and Lean Startup were in the field of management.

There'll be a problem if you are truly "unfamiliar with the jargon", whether you try to talk to people or submit a paper to a peer-reviewed journal. Likewise, if you write a book but/and without connecting to "the jargon", no one will take it seriously.

Why not get a PhD and learn how to do it from inside academia? The whole point of a PhD is to answer the question you are after if you skip the last couple words. If you don't think the effort is worth it then neither are your ideas.

You can also present at a conference, where you will get an opportunity to discuss your research with many people (as well as hear about and discuss theirs). Some conferences are meant for students and networking and have minimal peer review. The downside is the cost of travel and the conference itself.

There are also small workshops held by universities and institutes which one can easily attend and present a poster if you want, and possibly meet some big researchers in the field. They may be free or charge a (relatively) small fee. Just look at the webpages of the institutions near you doing similar research.

What do you mean by validation?

"I am not very familiar with the jargon and I can't quite communicate my ideas in a casual conversation" This is concerning, not because your paper doesn't use the jargon, but because it suggests that you haven't read enough of the existing literature to have gained a good understanding of the current state of the field you hope to extend.

If it's not based on statistics, then is it worth anything?  I am exaggerating a bit, but...

First, I am not from the field of psychology, but I assume that the research rules are equally applied to all fields.
A general comment: any idea you think is new -in any research area-, is more likely to collide with the fact that it has already been explored and patented -if you have a small experience in the field of course-.
Validating your idea does not necessitate a direct involvement in academia. However, it is important to know the academic process, which consists of:

Reviewing the state-of-the-art sufficiently. This means, reading the recently published papers (mainly from reputed journals and proceedings) and books by using specific search engines (e.g. Google Scholar) and references/cited-by of the publications you know. Please be aware that keywords might be different across different communities.
If you are not directly involved in research, you may contact researchers interested in your topic and idea. Btw. your assumption that they wouldn't even listen is wrong. Researchers and academics (regardless of their research area) are always open to new ideas. We (a CS research group) do this all the time, where we discuss with companies and individuals about new ideas and collaborations.
If you don't prefer contacting research groups and labs or you don't get an answer for any reason (which I don't it would happen), you can write the paper by yourself following what you have learnt in reviewing similar works (you can also check tutorial how to write a good paper). You will need to follow the journal or conference instructions (e.g. number of pages, etc.). You then submit the paper and wait a couple of months to get the first decision.

Now regarding your assumption:

Write a book. This is a non-scientific approach ....

It is incorrect if you aim to publish a scientific book. Generally, good publishers won't easily publish the work of unknown authors unless they publish it in a series which requires the acceptance of its editor. Here also, the work has to be proved by the editor to have the chance to be published.

Submitting a paper to a journal is not an unrealistic option. There are a vast number of reputed, peer-reviewed journals out there, each with a specific focus. You need to find the journal that will be the best fit for your ideas.

For eg: the journal Emotion Review specifically looks for theories, commentaries, reviews, and ideas, and is not particularly interested in new empirical studies.
It doesn't matter if your ideas don't involve statistics-based or empirical results, as long as you can find a journal that fits, and follow its guidelines.
Also, a lot of these journals have a double-blind review process. So the only thing that matters is the structure and content of your manuscript.

Not being acquainted with the jargon will be a problem. There's no harm if you've developed your ideas independently or if your vocabulary is a litte different - in fact, that could be critical to thinking outside of the existing conventions and creating a much-needed paradigm shift. But you still need to acquaint yourself with the work that's already been done in that area.

You need to explore, and review the existing literature, and figure out the existing concepts, ideas, and methodologies. This can seem daunting as an independent researcher at first, but the process gets easier as you go. You could take some courses online or access open universities' materials on research and scientific writing for some added help.
This will help you fine-tune and polish your own ideas - even if you decide that the existing concepts and constructs are worthless. (In this case, you can choose to critique them and propose your new models and terms.)
And when you know the jargon, you can communicate much more effectively and precisely, find mentors, and get collaborators interested in your ideas.

You could write a book to share your ideas, but at the end of the day you're still going to have to market it. Loads of books are published every day, content is burgeoning, and everyone has a hot take. You need to think about why anyone would invest their time and effort in choosing and reading your book specifically.

Conclusion:
You probably feel excited about your ideas and may want to get them across as quickly as possible, but the scientific process is more of a slow burn.
So start reading books, papers, journals, make notes, ask a lot of questions, be skeptical and stubborn and critically analyze what you're reading. Get acquainted with what people are doing/thinking and the different approaches/theories present in the field.
Write about this. Writing is a critical skill, and not only does it help you communicate your ideas, it also streamlines them and makes them crisp and focused. You need to be able to communicate your ideas without getting muddled and lost. Not just to experts or scientists, but also to a more layperson audience. And if you can't, this usually means that your ideas are still raw and need to be formed more clearly.
This is not going to be quick and easy, and it's unlikely that you'll have a clear picture or path right from day 1. But as you read/explore more, and write/summarize more, you'll slowly find the puzzle pieces falling into place.
Along the way you'll probably find researchers and authors you want to talk to or network with. You can probably form connections on social media sites like Twitter and LinkedIn or follow their blog if they have one. You may find conferences and seminars you want to go to. The process will just unfold itself as you go, and you'll find new options, avenues and opportunities.
Maybe you could even go for further studies and enrol in a PhD program - if that's feasible for you and your circumstances.

Try publishing on trade and industry magazines. Some do have a sort of review process.
Especially if your psychology ideas are interesting to marketing they might be picked up, and do write a book, it will be just for copyright, though.
Remember that academia is a vicious cycle full of insidious incentives to publish as many random papers as unnecessarily as possible, which is why a lot of practical research is being done outside of it now.