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I posted here yesterday for a totally different reason, so I'll be brief on the introductory piece. I'm a 4th year Ph.D student in Experimental Psychology who is slated to graduate this academic year. My experience and guidance at all levels up until recently has been different to say the least. This particular post is one that comes from a gap I've only recently seen in my training as an Experimental Psychology (soon to be doctorate). Thankfully, I don't see this affecting my admission to candidacy at all since I am already a candidate. I'm moreso concerned about how this may be seen when my relevant coursework will be reviewed come job application time.

I was recently asked by my current advisor (who took me after my first Ph.D advisor dumped me over a misunderstanding) if I took Multivariate Statistics. Upon reviewing my transcripts, it turns out that I never took a "higher level" stats course beyond the first ones at either the MA or Ph.D levels. I did not have much of a say as to whether I could take a second one given that my MA advisor was totally hands off and my first Ph.D advisor wanted me to just jump into my quals project (they do that instead of an exam in my program) after I voluntarily opted to retake graduate level statistics at my current Ph.D program in case my advisor wanted me to take more stats classes with my current program. The reason I'm inferring that this may be a potential problem is because, when I reviewed other Experimental programs, I saw that two stats courses were required of even the MA students (note this doesn't include Research Methods/Research Design courses) and upwards of three to four for Ph.D students.

Which brings me to my main question. How will employers review my transcripts? Will they note these potential shortcomings? I could try to argue for getting the department or graduate school to pay for another statistics course but I'm not sure if that will do more harm than good given their financial situation was not good at all.

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    Well, I never took a stats class in my PhD and nobody ever asked about any of my classes, period.
    – Jon Custer
    Commented Oct 9, 2023 at 14:31
  • @JonCuster I'm going to assume you're not trolling. What did you study?
    – zzmondo1
    Commented Oct 9, 2023 at 14:35
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    Experimentalist in Materials Science. But, really, I never had anyone ask about what classes I took or what grades I got. They hired me for my ability to do research.
    – Jon Custer
    Commented Oct 9, 2023 at 14:47
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    No one cares about your classes in PhD.
    – user479223
    Commented Oct 9, 2023 at 15:32
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    "No one cares about your classes in PhD." Except possibly you later in your career, when knowledge from those courses would be useful. (For example, some day when you want to write a paper in experimental psychology, but it requires sophisticated statistical analysis.)
    – GEdgar
    Commented Oct 10, 2023 at 0:58

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Two comments:

First, once you have your PhD noone will ever look at your transcript. The courses were necessary steps to create the real output: your thesis and your publications.

Think of it this way: What skills you could have gotten from that additional stats course would be valuable to an employer? Probably something you could pick up in half a day reading (or watching youtube). Even if you had taken the course, you would probably still forgot it when you needed it, and you would still have to spent that half a day reading. If an employer hires a PhD, then they want someone who can pick up what they need quickly, not someone who already knows everything (because that person does not exist).

Second, you are still worrying about stuff that you cannot change. Do yourself a huge favor and stop! You are only hurting yourself by doing so. There is nothing you can do to change your past decisions. Look forward, not back.

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    -1. I am a statistician that regularly struggles with lack of statistical understanding by psychology Ph.D. students, and no, you don't just pick statistical knowledge up by "half a day reading (or watching youtube)". To be more precise, that is exactly where a lot of statistical misinformation comes from that we at CrossValidated set straight day in, day out. Knowing you from CV, I am more than a bit surprised at this answer. Commented Oct 9, 2023 at 19:05
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    @maarten_buis Belated reply but I'm definitely going to take a step back from Stack Exchange after this page is either closed or is not taking replies at all.
    – zzmondo1
    Commented Oct 10, 2023 at 0:17
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    @zzmondo1 I am not suggesting you are not welcome here, you are very welcome. I am just worried about you. You seem to spent a lot of time on things you cannot change. I am suggesting you change your focus to "what can I do?" rather than "what did I do wrong?" Commented Oct 10, 2023 at 7:38
  • @MaartenBuis I understand now. I think a lot of it has to do with getting this far out and coming to the realization of "what have I done?" if that makes sense. I just want a different perspective on those things so I'm not stuck with those sorts of leftover questions in the back of my head.
    – zzmondo1
    Commented Oct 10, 2023 at 13:25
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    @Aqualone: I beg to differ. I am in exactly the situation you describe, having done a math Ph.D. and then pivoted to statistics without having had any stats during my studies. Statistics requires a very different mindset than math or natural sciences. I will agree that those subjects are a much better preparation for statistics than social sciences, but the "half day" idea is where all the statistical misinformation comes from that highly qualified software engineers and similar put onto the internet after having spent exactly this much time in learning. Commented Dec 21, 2023 at 6:33
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All hail stats! Joblessness and death to the non-stats-knowers!

Ahem, excuse me. In all seriousness, in the field of experimental psychology you are likely to do experiments that generate data and you will need to perform some statistical analysis. Most research psychologists find that they need a significant amount of training in statistics (so much so that some end up becoming quasi-statisticians). I would hope that both your undergraduate and PhD program have given you the requisite skill to get started on this, but you are correct that you might need to study some higher level statistics courses to get comfortable with all the material you will need. You should consider taking some additional courses if you have the time, or even just auditing courses if it is difficult to formally enrol.

As to whether your lack of higher level statistics will inhibit job applications, that depends very much on the needs and expectations of the particular panel looking at applications and their diligence in uncovering your present level of training. Some selection panels will look into the details of your academic transcript to see what courses you have done but many will look only at the overall degrees earned and the other aspects of your response to the selection criteria for the position. Many potential employers will not bother reading your transcripts (and might not even ask for them) and will instead assume baseline research competence from your PhD.

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  • I don't have the time to do so nor can I afford it at the moment sadly given that I get paid monthly at this full time SLAC position. It is definitely the case that I've gone hands on with generating data and have performed analyses. However, they've been correlations and/or regressions in SPSS or Excel. I will admit that I don't have much of a breadth in the way of other statistical skills, but I know how to get those done.
    – zzmondo1
    Commented Oct 10, 2023 at 0:48
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(Slightly edited after seeing Stephan Kolassa's comment)

If you apply for a job that requires multivariate stats, or whatever the topic of the second class was, then it might make a difference.

But even then, if you can show that you know the topic by picking it up during your research, the lack of this class won't make too much difference.

For jobs that do not require multivariate stats, it will probably not make much difference.

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  • Gotcha. Job lisitings I'm seeing never mention the exact stats background they are looking for in this case, which is why I was a bit concerned.
    – zzmondo1
    Commented Oct 9, 2023 at 18:31
  • OK. If they require some stats background, then I suppose the more the better. So the multivariate course might have been valuable. But you can still compensate.
    – toby544
    Commented Oct 9, 2023 at 20:52
  • That's good to know. The topic of the class was (indeed) multivariate stats. I've yet to come across jobs that explicitly require it. I might just see "courses in statistics" or something vague like that at best. It just worries me a bit since I saw it was a required course (or a vaguely administered "Stats II" course) at every other Experimental Psychology program.
    – zzmondo1
    Commented Oct 9, 2023 at 23:13
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Direct answer to the question that's asked: when you apply for a job, the employer will ask for your CV. They are unlikely to ask for a transcript. This means that they'll only learn that you have statistics expertise if you say you have statistics expertise on your CV (which you should, because people unfamiliar with experimental psychology might not see a relation between psychology and statistics).

Once the employer knows you have statistics expertise, they might ask you to demonstrate that expertise. This can take two main forms: either they send you a technical test, or they ask you about it during an interview. The missing statistics class can become relevant here, if they ask about something which you didn't learn.

In the unlikely event they ask for a transcript, it's improbable that they will hold the missing class against you, because the syllabus varies between universities. Besides, unless the reader also has psychology expertise, they probably won't know what's taught in a class (given only the name of the class and the course code).

So, the missing class matters insofar as you know less statistics than you would if you had taken that class - but that applies to every class that you didn't take.

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