How to Choose an R-Trainer?

July 22, 2014

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

by James Peruvankal

There are plenty of options if you want to learn R and are looking for training: your college’s statistics department, massive open online courses like Coursera, Udacity, edX, Datacamp etc. SiliconANGLE recently published an article about top R-training companies.

Let’s talk about how to choose a good R-trainer.

  • First and foremost is technical competency in R - In addition to having done a significant amount of R programming, the instructor should have an education in a quantitative field. The idea behind this is that the instructor will have had experience expressing non-trivial ideas in R. However, it is not necessarily the case that the most technically competent person is the best instructor.
  • Experience in teaching statistics - Learning R invariably involves working with statistics. So knowing where students can go wrong in understanding statistical concepts is a skill that greatly increases the effectiveness of an R Instructor. This skill only comes with experience. Joan Garfield's 1995 article in the International Statistical Review: How students learn Statistics is an excellent reference on what could go wrong in learning statistics and how to correct them.
  • Communication skills - The instructor should have the ability to clearly communicate complex topics in simple examples that students can relate to.  We recommend Gelman and Nolan's book: Teaching Statistics: A Bag of Tricks which promotes an activity based approach to teaching.
  • Evangelism - Passion generates passion. The enthusiasm of the instructor spreads to the students.
  • Teaching style and philosophy - From our experience in teaching and based on decades of research on how people learn, we have come up with our teaching philosophy. The most important factor is that people ‘learn by doing’. Ensure that hands-on learning is where most of the time is spent on.

At Revolution Analytics we are guided by the teaching philosophy presented in the following chart:


So, if you are serious about learning R, brush up on your statistics, be prepared to jump right in and start doing things on your own, surround yourself with people who are passionate about statistics and R, and figure out how to make the whole process fun for you. If you are teaching R and want to join us in our mission to ‘take R to the Enterprise’, see if you can fit in with our team.

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