Introduction to R

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

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
and
. 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

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
Leyla Azarang

Course duration

4 days, 09.00 - 16.30 hrs

Course costs

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)
 
R
emarks
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
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.

Course data in 2024

:

Introduction to R - Schedule June 2024

Monday June 3 - room Z4
Tuesday June 4 - room Z4
Thursday June 6 - room Z4
Friday June 7 - room Z4
From 9.00 - 16.30 hrs

Medical Statistics in R - Schedule June 2024

Wednesday June 19 - room Z4
Thursday June 20 - room Z4
Friday June 21 - room Z4 
MondayJune 24 - room Z4
Tuesday June 25 - room Z4
From 9.00 - 16.30 hrs

Registration

For NKI and AVL: You can subscribe for these courses in "

"of the AVL Academy

For AUMC participants or others: please send an email to

. The OOA will not pay for the course. We will send an invoice before the course starts. 

Cancellation

If you have registered and you cannot attend, please unsubscribe in the Leerportaal (NKI and AVL) and in case of AUMC, send an email to
 
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.

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