Using R for data analysis 2026

Introduction
R is an open-source, free environment/language for statistical computing and graphics. It provides a large repository of statistical analysis methods. The goal of the course is to teach students how the R language, extended by tidyverse package, can be used to build a report with a simple statistical analysis of data provided in a table. The course assumes no prior programming knowledge. This is not a statistics course! *(see comment below on page). Elementary statistics knowledge is necessary to understand examples.

After the course you will be able to:

• understand and write (tidyverse-based) R code
• know where to look for R methods to perform statistical analyses of your own data

• generate reproducible reports from your own data in HTML, PDF or DOC formats

   

The following topics will be covered:

• R expressions.
• R data objects: vectors, data frames (tibbles), lists.
• R Markdown for building reproducible reports.
• Data manipulation: filtering, sorting, summarising of a table; joining/merging multiple tables (with tidyverse/dplyr and tidyverse/tidyr).
• Visualisation: scatter plots, histograms, boxplots (with tidyverse/ggplot2).
• R packages: installation and usage.

Course material / Course structure
All study materials are supplied electronically only. The material will be covered in lectures and practical sessions. 

Duration
The duration of the course is 4 days.
The lectures will take place on campus, in the LUMC, in Lecture Hall 7.

The course is divided in 8 half-day sessions. During these sessions, the teachers are continuously available for lecturing and support.
 

SESSIONS 1-7: PRACTICE
The course will be given in a plenary format. Each session is divided into several short topics, and each topic is introduced as follows:

• a brief introduction/demo
• hands-on session
• a short Q/A segment, when needed
   

The students are encouraged to type the commands being presented and observe the effects, avoiding copy-paste as much as possible, own typing is essential to learn how to diagnose and resolve mistakes and errors.

SESSION 8: ASSIGNMENT
At the end of session 4 an assignment will be introduced. It is designed to simulate a real world data analysis project delivering a written report. In this session you’ll have the opportunity to finalise the analysis and your R Markdown report.

To achieve this, you will be carrying out these or similar steps:

• create an RStudio project
• create an R Markdown document – your report
• data understanding/exploration: import and study the provided dataset
• data manipulation: carry out necessary steps to generate your final dataset
• data exploration/visualization and descriptives (e.g. Table.1)
• answer the research questions 

• finalise your report

At the end there will be a general discussion with a Q&A session. 
 

Prerequisites
Participants must be able to use a laptop/computer capable of running recent RStudio.
See below for the RStudio Installation section.
 

Installation
Installation of R and RStudio software, including additional packages, is required before the start of the course. Resolving installation problems during the course may be impossible, therefore please follow the installation steps below a week before the start of the course. In some situations, intervention of the administrator of your computer might be necessary.

LUMC managed laptop – no admin rights
Installation of the R software via the LUMC Software Center is strongly recommended. This should avoid the following problem: Programs, such as R and RStudio may be installed on LUMC network drives instead of local drive 'C:'. In that case some functionalities may fail, in particular generation of R Markdown reports. A solution is to force the installation on your local drive such as 'C:', this however, may require administrator privileges which you may not have.  Alternatively, you may consider a separate laptop which is not administered on LUMC network for the time being and try to resolve the issue later with your system administrator. 

Personal laptop – you have admin rights  

• Install R: go to the R Project for Statistical Computing (https://www.r-project.org/) and follow the download and installation instructions.

• Install RStudio: go to the RStudio download page (https://www.rstudio.com/products/rstudio/download/#download), select a version of RStudio appropriate for your laptop, download it and then install. Please check whether you can start RStudio. 

   

Additional packages are needed for the course. During the course the participants will learn how to install packages but this process occasionally fails (because e.g.: additional steps are needed in a particular operating system, or there is lack of permissions to access some system directories, or other software is too old, …).
 

• Install tidyverse package: Start RStudio. Go to menu Tools/Install Packages... In the field Packages select tidyverse. Press Install. (Now, a lot of messages will be shown in the Console window - wait till it finishes). In the Console window type library( tidyverse ) and press Enter. Some messages might be displayed but when there is no error the installation is completed.
• Install packages needed for R Markdown: Start RStudio. Go to menu File/New File/R markdown.... A New R Markdown window is displayed. Press OK. Now, in case of missing R Markdown packages, you will be asked to install them. Finally, you will see an editor window with Untitled1 header. Put the cursor in that window, then click Knit. Some messages might be displayed but when later a window with some text and a plot is shown the installation is completed.
   

In case you encounter any problems with the installation, please contact your system administrator first.  If problems continue, please notify the speakers. 

Certificate of Attendance
To obtain a proof of participation, participation in all lectures and practical sessions is required. If you have participated in the full course, you will receive a certificate of attendance within two weeks after the course.

Language
Course material and lectures are in English.

Target group
Master and PhD students in the bio-medical sciences.

Organizing committee / Teachers

• Dr. S.M. Kielbasa (S.M.Kielbasa@lumc.nl)

• Drs. R. Monajemi (R.Monajemi@lumc.nl)

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* Interested in another statistics course? Please visit our website to check out the various courses that are offered by Boerhaave Nascholing.