Introduction to R for Data Analysis
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 )
Prerequisites
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.
Course lecturers
Renee X. de Menezes
Renaud Tissier
Vincent Pappalardo
Terry Chan
Course duration
4 days, 09.00 - 16.30 hrs
This course is not available online.
Course costs
Free: NKI or AVL researchers
€ 200.00 (PhD Students)
€ 300.00 (other researchers, postdocs etc.)
€ 600.00 (Non-academic participants)
Remarks
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 secretariaat.psoe@nki.nl 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.
ECTs
Participants who have a minimum of 60% attendance and successfully complete the final assignment earn 1.3 ECTs.
No medical accreditation.