Programming with R
The benefit of using a programming language such as R is that we can automate repetitive tasks. This course covers the fundamental techniques such as functions, for loops and conditional expressions. By the end of this course, you will understand what these techniques are and when to use them. This is a one-day intensive course on R.
Edinburgh, UK | October 11, 2019
- Conditionals: using
elsestatements in R
- Functions: what a function is, how are they used, and how can we construct our own functions.
- Looping in R: an introduction to the concept of looping in R. In particular
- The apply functions:
tapplyand other members of the apply family.
- Help: The help system in R can at first glance appear daunting, however, after the initial shock, R’s documentation is second to none.
- Project structure: Practical tips on how to structure a project.
By the end of the day participants will…
- have a thorough understanding of
forloops and the
- understand how the aforementioned techniques can be applied to their own data
- understand how these techniques will improve efficiency and results.
This course will be structured as follows:
- 9:00 — 9:15: Registration and coffee
- 9:15 — 10:45: Lecture
- 10:45 — 11:15: Coffee break
- 11:00 — 12:15: Practical 1
- 12:15 — 1:15: Lunch (not provided)
- 1:15 — 2:15: Lecture
- 2:15 — 4:30: Practical 2 (with a coffee break)
These times are intended to give a flavour of how the course is run and are subject to change.
The course follows on from the Introduction to R course. It is assumed that all students have attended this course (or have equivalent skills). This course is suitable for all fields of work. Previous attendees include biologists, statisticians, accountants, engineers & students, i.e., anyone who uses a spreadsheet!
- We started from the beginning and achieved a lot by the end. I’m not scared of R any more. It was actually fun!
- You cover all the aspects that we need to learn to get started.
- The course was excellent, as it has allowed me to do all the analysis and graphics for my PhD thesis in R, which has certainly saved me a lot of time and allowed me to do some advanced analysis that would have just been too difficult to do otherwise.