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My supervisor said to me that a supervisor isn't expected to help a student with such problems as errors in statistical packages (R, etc). I suppose it refers to all sort of data managing questions. I asked him, what if I am stuck, what should I do? Go to a stats teacher or do it on my own and he said do it on my own (Google it, etc, etc).

While I understand that I can't expect my supervisor to sit with me all day, I'm lost... Is it okay? Like, aren't there situations when you're just lost and need help? Especially when for him it will be a five minute solution while I can sit there for days and weeks, frustrated and helpless.

This attitude of his makes me anxious and self-doubting even more. Now I hesitate every time I want to ask him something.

I really don't know how to deal with this. I wonder if I'm just not suited for academia since I "can't work independently enough".

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    You mention a "stats teacher" - do you have questions about statistical analysis or do you have questions about programming? You wouldn't ask a stats teacher, either, how to handle an error message in R. See also the difference between StackOverflow and CrossValidated (stats.stackexchange.com).
    – Bryan Krause
    Mar 15, 2023 at 19:05
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    @Ben Oh of course, but that doesn't necessarily mean you should bother them with such things, unless perhaps you reach indirectly one of the many who, say, follow the R tag on SO or one of the R mailing lists.
    – Bryan Krause
    Mar 15, 2023 at 21:39
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    I wonder if I'm just not suited for academia since I "can't work independently enough". The same situation also holds in industry: you will usually have someone to help you at the beginning, but will be expected to figure a lot of stuff out on your own. But that is OK! Finding solutions to problems is a skill you have to (and can!) learn just the same as many other skills. Specifically, for error messages in R, it is usually very helpful to just google the error message (set your locale to English to get the exact English wording). Mar 16, 2023 at 9:35
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    It's not really clear to me what kind of supervision situation this is; the wording is rather ambiguous. Can you please edit the question to clarify? For example, I would expect more concrete guidance towards a bachelor student than a PhD student, and similar more concrete guidance from a post doc leading a small group than a professor leading an entire lab. Mar 16, 2023 at 10:31
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    @Blackhawk Most supervisors I know complain that their students don't ask for help when they get stuck. Lack of communication appears to be much more common than too much communication. And these kinds of remarks, "it seems kind of insulting to ask for help", are at the root of the issue. The supervisor can always make it clear what kind of help they will provide and what kind of help they will not provide, but "not asking for help by fear of being impolite" sounds like a terrible idea.
    – Stef
    Mar 18, 2023 at 10:26

7 Answers 7

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Your supervisor is correct. Most supervisors don't help at this level of detail. You have some options: take a class in that particular programming language/stats software (sometimes there are things like summer workshops you can enroll in), Google and get responses from listserves or somewhere like StackeExchange, or ask a peer.

One of the benefits to being a student is that there are usually peers or older students who you can form groups with. This is the benefit of sitting in a lab or PhD student offices - you will make friends and be able to help each other with these mundane roadblocks.

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    Actually my grad school peers and I still maintain a google chat, while most of our topics of conversation have evolved as our roles have shifted to faculty, we still occasionally ask each other about coding issues!
    – Dawn
    Mar 16, 2023 at 4:31
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    Good answer, except, taking a class in some language/package to try and track down one error is a non-starter. Mar 17, 2023 at 3:57
  • @DanielR.Collins - yeah, you should take that class before you use a language/package.
    – Davor
    Mar 17, 2023 at 9:56
  • Sure, but I get the sense this person needs some basic/beginner help if they are not sure how to debug.
    – Dawn
    Mar 17, 2023 at 15:39
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    My opinion is wildly uninformed, but it seems to me that gaining the skills to research and solve technical problems like this must surely be one of the beneficial outcomes of attaining a PHD.
    – Blackhawk
    Mar 17, 2023 at 16:10
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a supervisor isn't expected to help a student with such problems as errors in statistical packages (R, etc).

This is correct. Your advisor should look at your results, give you feedback on them ("this looks buggy!"), and suggest next steps. Or, even better, should discuss next steps with you. Getting from one wicket to the next is your job.

Especially when for him it will be a five minute solution while I can sit there for days and weeks, frustrated and helpless.

Don't be afraid to own your time. If you don't know much about software fundamentals, you can devote a couple of days or weeks to studying the topic. This may save time in the long run.

If you know the fundamentals but still can't solve something (even after many attempts), it is totally OK to ask for help. Seeing someone else's workflow can be very useful to you. But, the person you ask for help might not be your advisor -- it may be another student or post-doc. Some advisors haven't touched code in 20+ years and couldn't help you if they wanted to. Hopefully you can identify someone; having to figure everything out by yourself is really challenging, since you "don't know what you don't know."

I wonder if I'm just not suited for academia since I "can't work independently enough."

This is an overreaction; if you could already work independently, there would be no need to attend graduate school. It sounds like your advisor has thrown you in the deep end a bit, expecting you to learn how to use unfamiliar software to solve difficult problems with minimal guidance. This is mostly OK, so long as he understands that things will move slowly while you are getting up to speed. If he is pressuring you for instant results and insulting you for not already knowing these things, that's poor supervision on his part.

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One faculty I know used an "order of magnitude" approximation for when to go for help, loosely based on salary.

Suppose a faculty member is paid $50/hr, the graduate student is paid $15/hr, and the undergraduate is paid $8/hr. Actual numbers certainly vary on time, field, and location. Then, the grad/undergrad ratio is 1:2, the faculty/undergrad ratio is 1:6, and the grad/faculty ratio is 1:3.

Your advisor certainly can solve many of your problems, and probably quicker than you can, but doing so is not always the best use of resources. You are paid as a student to solve problems on your own, because what your advisor really needs is independent effort. If a grad student thinks a 1 hour meeting would solve their problem, it still might make overall sense to have the grad student grind away at it for 2-4 hours instead of taking up an hour of their advisors' time. An advisor might want their undergrad to work for an entire day without making progress before they come and seek out faculty time. Conversely, if you know this is a 20 hour problem for you, but a 1 hour problem for your advisor because you have genuinely different skill sets, then calling them in immediately might make perfect sense.

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    This seems surprisingly generous with the advisors' time. Mar 17, 2023 at 3:59
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    Careful with these kind of calculations. Students aren’t just there to get a job done; they’re there to learn to do a better job as they progress and for core topics to learn full stop. If I expect a student to need a skill say 50x during their work, or even need it to progress at all into more difficult tasks, things look very different. Mar 17, 2023 at 6:16
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There are multiple layers to the answer:

First, tools evolve fast, and when working at the cutting edge, your advisor can't reasonably be expected to know everything. Other answers are correct: find a community of other students with similar interests. Some papers will also include open source code, as a knowledge base that can help learn from those who came before.

However: that doesn't mean that your advisor or department is powerless. Many big schools are developing ways to help: semi-official orgs (like Software Carpentry) offer workshops in programming or stats tools, run by and for students. Some departments will also have dedicated stats or methods consulting: either through a local employee who helps with coding questions, or another department. (where I am, several stats groups have "consulting" hours where they invite interesting mathematical problems for potential collaboration) Ask around.

My rule of thumb: even if I don't know the answer, I try to build a collection of learning resources that prior students found useful (oreilly has some good introductory R books, for example- your library might even have a way to read them free online).

I've seen too many faculty cover for lack of knowledge with bludgeons like "it's easy" or "if you're smart you'll figure it out". If a tool or skill is critical to your group, expect to get asked this question more than once, and help foster those connections that make a training program come alive.

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As a rule of thumb the concrete, low-level help from supervisor to student is inversely proportional to the seniority of supervisor and student. A bachelor student will need more help while a PhD student will be expected to work largely independently, for example.
Crucially, there's a point at which "you're the expert now" and there simply is no-one else to ask. Much of university/higher education aims at getting you there.

So it is usually not really about how long it takes an expert versus you to get the job done. Most of the time, it's about how long it takes you to learn the skill to get the job done; getting the job done is a nice side-effect and learning opportunity but not necessarily the goal itself.

In this regards, try and see both experts and supervisor as tools – just like a book on the topic, or Google, or forums, or peer groups, or courses, or similar. Notably, human experts and supervisors are a much more limited resource than, say, an instant search engine 24/7 available. As a rule of thumb, your first instinct should always be to start at the more available resources and move to more expert resources as a) your grasp of the topic increases to narrow the issue down and b) the necessity for expert advice to solve the issue becomes clear.
So yes: You should try and do it on your own. Only if that fails, then go ask an expert.


That said, your supervisor should not just be an elusive mastermind that you do not dare talking to. Learning to work independently includes learning when you are at your actual limits. Your supervisor might want you to push your limits to improve them but the point is not to ignore those limits. So:

This attitude of his makes me anxious and self-doubting even more. Now I hesitate every time I want to ask him something.

No matter where you are in your studies, this is something to talk about with your supervisor. That is not about putting blame on them or you, but about making you learn how to deal with such a situation yourself. Be honest, be upfront, ask for their advice and make them aware there is a problem that keeps you from working independently.
Ultimately, your supervisor is not there to give you a fish. They are not there to teach you how to fish. They are there to teach you how to teach yourself how to fish.

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Is this your degree, or your supervisor's?

If the answer is the former, why are you expecting your supervisor to put in effort to complete your degree for you?

Their job is to guide the direction of your studies, not babysit you through the day-to-day minutiae involved in them. If the concepts that you are having problems with are something you can reasonably be expected to already know or figure out on your own as part of your degree's focus, it's your responsibility to put in the effort to master them.

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Read the documentation of the packages. Test the packages - not only check if they provide a sound result (e.g. in comparison with NIST's Statistical Reference Datasets), but to get familiar enough to work with them. Consider attending user group meetings in your area (a directories, R-Ladies, or the RUGS program), or joining a discussion group - either linked to the program (like r/rstats on reddit), or "just statistics"/ agnostic to the software you use like crossvalidated* - even if your initial intend might be to listen / read only, they may be a source of inspiration (like the R journal) and help.

If you are a beginner in R, perhaps the starter workshops Programming with R and R for Reproducible Scientific Analysis by software-carpentry.org help you to get started. There equally are many recordings of tutorials/conferences on sites like youtube, too.

* Said sibling site cross-validated offers to tag questions with R for which R is "considered as a critical part of the question or expected answer" but [the question is] "not just about how to use R". So far, the page hosts 28k+ questions and answers. With a minimal reproducible example, there are good chances to obtain help specific to the statistics.

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