What is R?
R is an open-source, free environment for statistical computing and graphics. It provides a large repository of statistical analysis methods, both classic and new. However, R has a steep learning curve, due partly to its using a command-line type of user interface, rather than the usual pull-down menus. This 3-day course aims at helping researchers climb this curve, enabling them to perform basic data analysis and graphic displays at the end of the course, as well as giving a platform from which they can deepen their R knowledge later on if necessary. Participants will also learn how to make dynamic reports, making their analysis transparent and reproducible.
Goals & Topics
After the course you will be able to:
• understand and write simple R programs
• use R to perform basic statistical analyses of your own data tables
• generate analysis reports from your own data in html or pdf formats, using RMarkdown
We will cover the following topics:
• R expressions and formula objects
• R data objects (vectors (arrays), data frames (tables), lists, matrices) creation and usage
• R functions for descriptive statistics and linear model fitting
• installing additional libraries
• histograms, scatter plots, boxplots (in pure R )
The course requires elementary statistics knowledge, but assumes no prior programming knowledge.
Participants must bring their own laptops capable of running R and RStudio. Please install R (from the Comprehensive R Archive Network-CRAN, for example from this mirror) and download and install RStudio before the course. Participants should also install the R package RMarkdown prior to the course.
Who should attend
Researchers who need to run their own statistical analyses, and want to do it in a transparent and reproducible manner. While most participants tend to be PhD students and postdocs, more senior researchers can also greatly benefit from the course.
Renee X. de Menezes
4 days, 09.00 - 16.30 hrs
Free: NKI or AVL researchers
€ 200.00 (PhD Students, excl. 21% BTW)
€ 300.00 (other researchers, postdocs etc., excl. 21% BTW)
€ 600.00 (Non-academic participants, excl. 21% BTW)
As we can accept a limited number of participants, we suggest those interested to register as soon as possible to guarantee a place.
NKI participants can register via the Learning Portal. Other participants should send an e-mail to email@example.com to register.
If you have registered and you cannot attend, please send us notice as soon as possible so that we can cancel your registration. Note that there is a no-show fee for those who cancel within less than 2 weeks prior to the starting date.
Participants who have a minimum of 60% attendance and successfully complete the final assignment earn 1.3 ECTs.
No medical accreditation.