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Feasible to Self-Teach Materials During the Semester?


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Hi. I am wondering how practical it is to learn new materials on my own during the semester, in addition to the first-year coursework and teaching I will be doing.

I am starting my doctoral program this fall with 3 courses in our psychology department. My adviser and I agreed, however, that sometime this or next year I could take some biostatistics courses to better prepare myself for the actual research projects. Hearing about my adviser's current projects and works, I thought that I need to catch up a lot in biostat and programming to have proper background knowledge for my future works. That's why I wondered if I could start early on my own, such as learning from a biostat textbook or an online programming course now and during the academic year, but would it still be practical during the semester given the first-year workload and teaching? Thanks for any input!

Edit: I asked my adviser if I need to start early on anything. The answer is not really...anything will be fine.

Edited by schenar
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8 hours ago, schenar said:

Hi. I am wondering how practical it is to learn new materials on my own during the semester, in addition to the first-year coursework and teaching I will be doing.

I am starting my doctoral program this fall with 3 courses in our psychology department. My adviser and I agreed, however, that sometime this or next year I could take some biostatistics courses to better prepare myself for the actual research projects. Hearing about my adviser's current projects and works, I thought that I need to catch up a lot in biostat and programming to have proper background knowledge for my future works. That's why I wondered if I could start early on my own, such as learning from a biostat textbook or an online programming course now and during the academic year, but would it still be practical during the semester given the first-year workload and teaching? Thanks for any input!

Edit: I asked my adviser if I need to start early on anything. The answer is not really...anything will be fine.

Unless you're exceptionally disciplined, your day to day responsibilities may place ever increasing pressure on your self study. I therefore recommend that you establish a modest plan with limited goals over an ambitious plan. For example, find a couple of resources (analog or digital) that you can use as references while you read works by your adviser and his peers. Work on familiarizing yourself with basic terms and concepts while leaving aside the nuts and bolts in depth knowledge for later. (Focus on the what rather than the how.)

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Many thanks @Sigaba for your perspectives! You are on point that I should only work towards being on the same page with my adviser, now that the problem is that I still could not communicate or discuss works with my adviser. I will keep that in mind while trying to fit any extra materials into my schedule.

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  • 2 weeks later...
On 7/22/2018 at 4:37 AM, schenar said:

Hearing about my adviser's current projects and works, I thought that I need to catch up a lot in biostat and programming to have proper background knowledge for my future works. That's why I wondered if I could start early on my own, such as learning from a biostat textbook or an online programming course now and during the academic year, but would it still be practical during the semester given the first-year workload and teaching? Thanks for any input!

So when I started my master's I had basically no stats background and I did end up taking a biostats course my first semester. However, what I learned in that course was not extremely helpful for the types of analyses I ended up doing for my thesis. I honestly didn't really learn my analyses until I had my full data-set collected and could start working with it. Also I was able to learn the most about my analyses on winter and summer breaks when I could dedicate entire days to learning new programs and such so it may be hard to juggle self-teaching yourself the analyses and programming you would like to learn during your first year with having to also juggle your own coursework and teaching.

Instead if you want to start getting acquainted with the future stats you will be doing I would suggest asking your advisor or a fellow labmate for a data-set that you can use for practice and then try to learn the types of stats you will need on school breaks where you can dedicate entire days and several days in a row to fully immerse yourself in these new methods. That's my suggestion since it worked well for me when I had my data-set so I don't see how it wouldn't work for practice data!

Edited by FishNerd
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  • 2 weeks later...
On 8/8/2018 at 11:48 AM, FishNerd said:

So when I started my master's I had basically no stats background and I did end up taking a biostats course my first semester. However, what I learned in that course was not extremely helpful for the types of analyses I ended up doing for my thesis. I honestly didn't really learn my analyses until I had my full data-set collected and could start working with it. Also I was able to learn the most about my analyses on winter and summer breaks when I could dedicate entire days to learning new programs and such so it may be hard to juggle self-teaching yourself the analyses and programming you would like to learn during your first year with having to also juggle your own coursework and teaching.

Instead if you want to start getting acquainted with the future stats you will be doing I would suggest asking your advisor or a fellow labmate for a data-set that you can use for practice and then try to learn the types of stats you will need on school breaks where you can dedicate entire days and several days in a row to fully immerse yourself in these new methods. That's my suggestion since it worked well for me when I had my data-set so I don't see how it wouldn't work for practice data!

Great I never clearly realized this, and it should be a more efficient starting with getting to know the problems first. I will make sure to add this to my question list for my adviser once we meet soon. Hope the semester goes well for you.

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