Introduction into R

With over two million users worldwide R is becoming the leading software package for statistics and data science. It is freely available and has many utilities and possibilities for e.g. basic and advanced statistical analysis; creating sophisticated graphs; data handling; and writing software. As such R is a very convenient software package since it allows you to create scripts for data handling, analysis, and visualization and to have your results and figures for your paper in one run, which cannot be done with statistical packages like SPSS, SAS, or Stata.

However for many researchers it is not directly clear how to use R, because of the R language and the way of reasoning. We would therefore like to introduce the students to and familiarize them with R. After finishing this introductory R course, you will master some very valuable R skills and will be ready to do your own data analyses.

This course is aimed at people who'd like to start using R. No previous experience in programming languages or data science is required, but knowledge of basic statistics (e.g. Student’s t-test, chi-square test, correlations, regression analysis) is required.

1)      After completing the first part of the course “Introduction into R”, the students can perform basic analyses in R.

In the first part of this course you will learn the basics of R through short lectures and many computer exercises. The following topics will be treated: the R language, R variables (objects), R data structures, reading and writing data files, manipulating datasets, performing basic statistics (only one day!), making graphs, simulations, and creating functions.

2)      After completing the final assignment of the course “Introduction into R”, the students are able to apply R on a real life database.

In the second part you will be given an assignment (case study) that challenges you to utilize the lessons from the first part. You will work out the assignment together with a fellow student under the supervision of the teachers. The end product will be the script of the assignment and you will get feedback on this script.

NB: the lectures are completely onsite, NOT online.

Examination: participation is required (90% attendance). Script will be evaluated as pass/fail and grade upon request.