Introduction to R

English-language course

Introduction

The R programming language is written by and for (data)scientists as a powerful tool for data science, statistics, and data visualization. R is free and open source, which means professionals around the world are continuously updating and adding functionality. With R, you can transform and investigate your raw data to gain actionable insights that drive intelligent decision-making and innovation.

In this beginner's course, you will be guided through the basics of importing data, cleaning and restructuring data, visualizing and summarizing your data, and finally applying statistical models to your data.

Result

At the end of the course, you will not only be able to work with R, but you will also be able to expand your knowledge in your specific field.

Interactive Learning Experience

This course relies heavily on highly interactive (online or hybrid) sessions where we review what you’ve done in the reader. During a review the teacher will share his screen and go through the code asking you by voting and chatting to find the error or complete the code. These reviews are used to rehearse material, show tips and tricks, warn for common mistakes, explain error messages, show how to use the helpfiles and the program (IDE) in general, and overall to motivate you to keep up the pace. Participants report they are highly involved during these sessions and the course is consistently highly evaluated. On average this course is rated with an 8.2 (10% gives a 10!) by students, PHD’s and other employees alike.

Practical Information

Goal

This introduction course is for everyone who wants to (re)learn the basics of the programming language R needed for data handling. This is useful for those new to R, or for those who have worked with R but never got the chance to get a good grasp on the basics themselves.

Content

Introduction to R and R Studio
R Essentials / Basics
Reading data from files (using readr and openxlsx)
Data transformations (using dplyr and tidyr)
Exploratory data analysis: graphics (using ggplot2)
Exploratory data analysis: despriptive statistics
Statistical tests (how to run the tests, not how to interpret them)
What's more (other useful packages and more classical programming)

Prerequisits

None, but an idea of what you’d like to do with R would be nice.
Please note R has a steep learning curve. Expect you’ll need 2-4 hours between sessions to prepare for the next one and plan accordingly. Please be kind to yourself and allow yourself at least 48 hours to complete the course.

Enrollment and course fee

Fill out this form to enroll

You can unenroll until 8 days prior to the first session.
Late enrollments are fine, but please also contact the teacher to avoid the risk of being overlooked.
Participants will receive the course material via email a few days before the course starts.

For more information, you can email Theo van Mourik (t.j.van.mourik@rug.nl).

Prices for individuals

€100 BSc/MSc student at UG, other Dutch University or Hanze Hogeschool
€300 PHD-student at UG or other Dutch University
€650 Employee UG or other Dutch university/UMCG/Hanze Hogeschool
€650 UG Alumni
€1250 Other participants

Prices for groups

20 or more PHD’s €200 pp (minimum price of €4.000)

10 or more employees €400 pp (minimum price of €4.000)

20 or more employees €250 pp (minimum price of €5.000)

5 or more others €1.000 pp (minimum price of €5.000, we’ll also need to send a separate contract for this)

When enrolling a group of participants, you need to provide a single financial contact person/cost center number and the mailing addresses of all participants. You can enroll a group using the normal enrollment link.

You can also request a customized course and discuss dates, audience, and content. For more information mail Theo van Mourik (t.j.van.mourik rug.nl). This is also possible within the curriculum.

Date, time and location

Below you will find the dates and times of the upcoming courses. The content of these courses remains the same each time.

If these dates do not suit you and you would like to be notified of future courses, please contact the coordinator, Theo van Mourik (t.j.van.mourik@rug.nl).

August 2024: 2 week course

All sessions are online, last 4 hours, and each requires 3 to 4 hours of preparation.
All presentations are given via the Kaltura classroom (no account needed) and can be followed online.
All presentations will be recorded and the recordings will be available for about 6 months after the course.
You will receive a certificate of attendance for attending 5 out of 6 sessions or (if preferred) after successfully completing a final assignment.

Session	Date (time 9:00 - 13:00)	Preparation
1	Mon August 26	Install R and R studio or start in UWP/VRW
2	Wed August 26	H 1 – 2.7 Intro and Basics
3	Fri August 30	H2.8 – H 3 Basics and import Data
4	Mon September 2	H 4 Working with tables
5	Wed September 4	H5 Graphs
6	Fri September 6	H 6 – 8 Descriptives, tests, programming

November 2024: 3 week course

- All sessions are online, last 4 hours, and each requires 3 to 4 hours of preparation.
- All presentations are given via the Kaltura classroom (no account needed) and can be followed online.
- All presentations will be recorded and the recordings will be available for about 6 months after the course.
- You will receive a certificate of attendance for attending 5 out of 6 sessions or (if preferred) after successfully completing a final assignment.

Session	Date (time 9:00 - 13:00)	Preparation
1	Tue November 12	Install R and R studio or start in UWP/VRW
2	Fri November 15	H 1 – 2.7 Intro and Basics
3	Tue November 19	H2.8 – H 3 Basics and import Data
4	Fri November 22	H 4 Working with tables
5	Tue November 26	H5 Graphs
6	Fri November 29	H 6 – 8 Descriptives, tests, programming

January 2025: 2 or 3 week course

There may be a course in January, but it has not yet been scheduled. If you would like to be notified about this or other future courses in R (or Python), please send an email to the coordinator, Theo van Mourik (t.j.van.mourik@rug.nl).

March 2025: 12 week evening course

This evening course is specially designed for lifelong learners who work during the day but still want to learn R. To accommodate the late hour, this course is given in a more informal manner ('gezelllig'). If desired, some key words can be translated into Dutch during the presentations, and participants can ask questions in Dutch if that is easier.

The evening course is held weekly on Tuesday evenings from 19:00 to 21:00 (online) and requires 1 to 2 hours of preparation per session.
Sessions 1 and 7 are hybrid. For these sessions, you can still participate online, but you can also join in person at the Zernike Campus in Groningen. Location: Mercator Building, room 5415.0031 (Landleven 1 Groningen).
All presentations are given via Blackboard Collaborate and can be followed online. Even if the sessions are held on-site, you can always choose to join online.
All presentations will be recorded and the recordings will be available for about 6 months after the course.
You will receive a certificate of attendance for attending 9 out of 12 sessions or (if preferred) after successfully completing a final assignment.

Session	Date (tijd 19:00 - 21:00)	Preparation
1	Tue March 4 (hybride)	Install R and R studio
2	Tue March 11	H1-H2.3 Intro and Basic vectors
3	Tue March 18	H2.8 dataframes, factors and formulas
4	Tue March 25	H2 – H 3.1Read and write CSV
5	Tue April 1	H3 (optional time to catch up)
6	Tue April 8	H4.4 Dplyr, filter, select, summarise
7	Tue April 15 (hybride)	H4 Tidyr, join and restructure tables
8	Tue April 22	H5.4 Basic graph
-	Tue April 29	GEEN LES I.V.M. VAKANTIEPERIODE
-	Tue May 6	GEEN LES I.V.M. VAKANTIEPERIODE
9	Tue May 13	H5 Graph with extra's
10	Tue May 20	H6 Descriptives
11	Tue May 27	H7 Statistical tests
12	Tue June 3	H8 Extra's and programming

More information

For more information on this or similar courses, please mail the coordinator, Theo van Mourik (t.j.van.mourik rug.nl)

Last modified:

21 May 2024 2.20 p.m.

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