Crash Course in R

If you want to learn programming in R and have no knowledge, this course is for you. You will learn how to load, access, explore and visualize your data, and you will understand basic programming terminology and online help.

This course is aimed at people with little to no knowledge of programming in R language and little to no experience with programming. We will introduce basic concepts such as variables and functions, how to use command line, how to write and share scripts and how and where to look for help. Later, we will learn about various data types and data operations, and we will finish with basic exploration and visualisation of datasets. After finishing this crash course, you should be able to load, access, explore and visualize your data. You should also understand basic programming terminology and online help and be able work on projects in R on your own.

ECTS
2
Level
Crash Course
Site
Face-to-Face & Online

Opportunies to attend this course

Lecturers

Lukáš Hejtmánek

CEBEX
Czech Republic

Course details

Topics covered


Introduction to R

Basics of Programming

Working with Variables

Working with Vectors

Loading and Saving Data

Working with Data Frames

Introduction to Visualisations

Basic Descriptive Statistics and Data Reporting


Schedule


Each lecture lasts 60 minutes. Morning lectures start at 8:30 and finish at 12:30. Afternoon lectures start at 13:30 and finish at 17:30. If not set otherwise, the break after each lecture lasts 30 minutes. All times are in Central European Time (CET).


ECTS requirements


To obtain the ECTS, a student has to get in total at least 60% of all available points which are being awarded for the following activities:

- attend all lectures (12 hrs. of WL / 2 pts. per hour, 24 in total)

  • - submit 2 homeworks (4 hrs. of WL / 8 pts. per homework, 16 in total)
  • - final exam (30 hrs. of WL / 60 pts)


Literature


Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage publications.


Software Requirements


The course will require you to install R (https://www.r-project.org/) and a free version of R Studio integrated development environment (https://rstudio.com/products/rstudio/). We will go over the installing process together during the first hour, but feel free to familiarize yourself with the websites and make sure your PC/Mac/Linux version is among the supported ones.

Questions? Shoot us a message