How to do research

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Every research project should aim to be written up as a paper eventually (Paper: article in a scientific journal). Therefore, planning a paper and planning a project are intimately connected.

These are the steps that I usually go through for each research project:

(1) I have an idea, or intriguing observation, or puzzling data in another study. I develop this into a clear question with hypotheses for the outcomes. I think about feasibility and impact of answering this question, and decide on principal methods. Accept a lot of guidance from your current or future mentors on what is a good project. Actively seek that guidance if it is not given right away. This is the part of research that most benefits from a good knowledge of the literature. Bring in your own creativity and ideas, but accept advice on which ones should be pursued.

  • Undergrads: assume that you cannot do this by yourself. Choosing the right question is something that is very hard without a lot of experience. Do suggest ideas you have to your mentor(s), however. Model your ideas on previous types of questions that your lab has studied. Remember each project answers only a very specific question.
  • Grad students: assume that you are at the beginning of learning to do this. Get a lot of feedback. Do not assume it is easy, or that you can ‘try out’ a lot of different projects. This step, coming up with the right question and the right hypotheses, can make your research easy and productive or a hard slog.
  • Postdocs: your mentor will likely assume that you are willing to do this, that you will take leadership in your project and come up with specific questions with little input from your mentor. However, it is always a good idea to get feedback.

(2) I find who my immediate collaborators will be. Who can teach me the methods, who has the equipment, who has the time to actually collect the data, etc. Make the roles, expectations, and reward for each person participating clear; define who is ‘leading’ the project. The project leader checks that everyone does their job on schedule, that the parts fit together and the project works out, and writes the first draft of the manuscript and thus becomes first author on the paper in the end.

(3) Develop the specific experimental plan, including sample sizes, methods of measurement, precision, planned statistical tests. Make sure you have and understand all equipment, experimental subjects, space in the lab, software needed. Sign up for equipment use if it is shared equipment.

(4) Do it. After the first round of tests/measurements, assess if the methods is working. If not, revise and start again. Do not waste time: once your experiment has started, it is generally best to crank through, do the highest sample size feasible (in our field there is rarely a prior estimate of effect size, and rarely a case where the highest feasible sample size is unnecessarily large). Observe good rules of data management and record-keeping.

(5) If you did steps 1-4, the analysis part should be pure joy. You have a data file in the computer that tabulates the data you need for your analysis, and you know what analysis you are going to do. Now you really test your hypotheses, which, ideally, will lead to a fascinating outcome no matter the results of the stats test. Often you have to do a couple of intermediate data formatting/summarizing/analysis steps before you get to the final p-value. But: do not be distracted from your well-planned goal. If there was a test that will distinguish your hypotheses, and you checked that the methods worked, then the outcome of the test tells you what your conclusion is. Do not second-guess it or spin it. However, there may be new observations or interesting patterns you didn’t plan on but that also answer interesting side questions. Sometimes the side questions end up more interesting than the initial question. Think hard about whether you need additional experiments to draw appropriate conclusions here though, since you didn’t plan for this and thus presumably your experiment and controls are not ideal for answering these additional questions.

(6) Start writing your paper.

 

 

 

Other people's advice:

Basic experimental design by AR Goldsmith

Find the right literature and read it regularly - tipps from Brian Enquist