Yesterday was my last day of academic teaching.

Although I keep doing in-house or company training (statistical computing only), I’m done with my regular lectures for this year. It was a long journey since October as I was in charge of 4 courses (around 90 hours in total), plus extra training for a private company. During the same period, I managed to work on two textbooks (basically related to this course) while working hard to get things done at my work.

But why do I keep teaching a lot, even if I have a full-time position? First of all, I like teaching and interacting with students on practical examples. This is a truly rewarding experience to be able to discover a whole new interpretations or think of new analyzes. Moreover, this is a way to engage in new directions to answer a particular question which is not necessarily part of your area of expertise. Finally, as for consulting, I “learn a lot, [and my] brain is maintained at a suitable level of activity.”

I have always devoted a fair amount of time to help students solving practical problems, which may range from computer issues to specific statistical questions which were not part of my course.
Each time, I remember some words I read on William Dupont’s webpage,
Statistical Modeling for Biomedical Researchers (see the first handout in PDF version):

(…) [P]lease ask. I would very much like to minimize the time you spend struggling with Stata and maximize the time you spend learning statistics. I will be available to answer questions at most times on days, evenings and weekends.

#### See Also

»

Data cleaning techniques
»

Writing a Book
»

Bad data handbook
»

Data science at the command line
»

Statistical questions in evidence-based medicine