Introduction to R
R (https://www.r-project.org/) is a programming language and software environment for carrying out computations, manipulating and analyzing data, and creating various types of plots and graphics. R has become the 'lingua franca of statistics' and the software of choice for analyzing data in various disciplines.
Moreover, R is free, open-source, and runs on various platforms (Windows, MacOS, Linux, etc.). However, for many researchers, getting up and running with R remains a hurdle due to the command-driven nature of the software. The purpose of this course is to lay the necessary foundation for becoming a proficient R user.
- Instructor Dr. Wolfgang Viechtbauer
- Intended for researchers, Master and PhD level students, data analysts/scientist, and essentially anybody interested in learning how to work with R.
- Intended for PhD candidates (Promovendi) of FHML, MaCSBIO, M4I and MERLN
- Three full days (09.00-17.00), 23-25 October 2019
Familiarity with basic statistical concepts and methods as used in the health, social, and natural sciences is helpful when following the course.
Course participants should bring a laptop with the current version of R installed (which can be downloaded from https://cran.r-project.org/). Also, while not necessary, installing RStudio (an integrated development environment for R) is highly recommended (which can be downloaded from https://www.rstudio.com/products/rstudio/download/).
Dr. Wolfgang Viechtbauer
Department of Psychiatry and Neuropsychology
Phone: +31 (43) 388-4170
- history of R
- basic data structures
- data import/export
- data inspection
- data manipulation
- graphing data
- t-tests and analysis of (co)variance (*)
- linear regression (*)
- analyzing categorical data / logistic regression (*)
- survival analysis and Cox models (*)
- mixed-effects models (*)
- add-on packages
- basic programming structures
- writing functions
- writing documents with Rmarkdown
(*) Emphasis here is more on the general syntax as used in R and less on the statistical details of the various procedures.
Three full days (starting at 9:00 and ending around 17:00, with a lunch break around 12:00 and coffee/tea breaks as needed).
Interactive hands-on lectures.
There are no required readings but the following book is a popular reference:
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. London: Sage.
Phone: +31 (43) 388-5613
Available: Mondays, Tuesdays, and Thursdays from 8:30 to 12:00
Maximum number of participants: 25
* Please note: when you subscribe, you will receive a response from the aioonderwijs emailbox after 17 September 2019.
PhD candidates (Promovendi) of FHML, MaCSBIO, M4I and MERLN: no fee
Master students: no fee (*)
(*) PhD candidates and other participants are given preference. If some spots are still available, then Master students can apply.
October 23 and 25: N4.22, UNS 60
October 24: Co Greep meeting room (M 5.01, UNS 60)
All course days are from 9.00-17.00. You need to bring a (fully charged!) laptop.