Keep your data tidy, Part II

My previous post on tidy data didn’t at all touch on rule 3, “Each type of observational unit forms a table.” The example I gave had only one observational unit, the weekly temperature measurements. Frequently, however, we have data corresponding to multiple observational units. In this case, it is important that we store them in separate tables, and that we know how to combine these tables for useful analyses.

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Surviving the pre-tenure years at an R1 university

A few days ago, Pröf-like Substance asked for posts with suggestions on how to survive the pre-tenure years. I went over my blogging history and realized that I hadn’t really written anything on this topic yet. Most of my advice to date is targeted at more junior scientists. So here is my attempt at giving some suggestions on how to make the most out of your years on the tenure track.

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Eat more gluten? Maybe not.

A recent article in Time magazine argues that “gluten free” is a fad and should die. While the author makes a few good points, overall I think he misses the mark. I agree with the author that when it comes to products where the main ingredient is wheat (in particular bread, pasta, pizza base, cereals, cookies, cakes), gluten-free replacements usually aren’t that healthy. These replacement products are frequently made of rapidly digestible carbohydrates and tend to be nutrient poor. However, what the author fails to mention is that the products being replaced are also made of rapidly digestible carbohydrates and are nutrient poor. There’s really not that much of a difference between gluten-free bread made of tapioca flour and millet and regular gluten-containing bread made of wheat flour. Most people would be better off avoiding both.

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Share your preliminary work with other people, even if you think it’s crap

It’s quite common for me to have students tell me “the analysis didn’t work out” or “the figure looks bad” or “I don’t have any useful results.” And it’s also quite common for the students to be wrong. Sometimes, students have amazing results but are all disappointed because the results aren’t what they had expected. These students fail to see the data for what they are. More commonly, the students may be right in that the data aren’t that great, but usually I can see something in the data that the student didn’t. In either case, it is important that we look at the data together, because jointly we will see more than either of us individually would have seen.

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How to develop a research question, Part II

After my last post discussing how to develop a research question, Sergey Kryazhimskiy asked me to write about how to find the rare good research idea among the many mediocre ones. The truth is that I don’t really know how to do this. If you do, please tell me. I’m sure I could strengthen my research program by picking better problems. Nevertheless, despite my ignorance, I’ve had a reasonably successful career to date. And it was probably not entirely due to sheer luck. So this should give you hope. Even if you don’t know how to pick good problems, you may succeed in science nonetheless. Just work on the problems that seem important to you and hope for the best.

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How to develop a research question

One of the most daunting prospects for a fresh graduate student is having to develop a solid research question [1]. In my experience, many graduate students feel like they don’t even know where to start. The literature can seem overwhelming, everything has already be done by somebody, and in any case it’s impossible to really know all the literature there is anyway. Making matters worse, almost every cohort or lab inevitably has one or two students who just seem to be fountains of good ideas, who constantly come up with new research ideas they want to pursue. As a result, students who are less inventive or less imaginative can feel like they’re not cut out for a career in research, they’re never going to have the necessary ideas to sustain a research program.

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How to pick a thesis committee

I was asked the other day what factors to consider when picking a thesis committee. And I realized that this is not a question I have pondered a lot. Normally, when one of my students needs to pick a committee, I just recommend people that seem a good choice. I don't have a properly thought out, systematic framework to steer the selection process. So with this post I’ll try to develop a more systematic approach to this question.

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6 reasons to do your graduate work in the lab of a junior PI, and 6 reasons not to

One of the eternal questions of graduate schools is whether you should work with a junior or a senior PI. I have commented on this question before and argued that either decision can be the right one. Here, I present a more comprehensive list of arguments for and against. As you’ll see, there are plenty of arguments going both ways. You may assign more weight to some than others and thus arrive at a decision that is best for you. Ultimately, I think it doesn’t matter too much; there are other factors that are more important, such as whether you enjoy and fit in with the lab’s culture and approach to research, collaboration, publication, and so on.

 

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