CESSARi project: Introduction to the R software for statistical computing
Welcome!
This course aims at addressing the basic aspects of proper data analysis using the R software for statistical computing. It will follow a blended learning approach, i.e. we will combine phases of online learning and classroom teaching. On this website you will find the entire course material which will enable an individual course preparation on beforehand.
The course starts with an online meeting (via Zoom, link see below) on July 30th (6pm-7pm), with the aim to present the course outline and to give useful hints for the start. A 2-day classroom course on August 4th and 5th will conclude the workshop. The focus of this attendance course is on supervised hands-on exercises with the statistical software R.
The overall objective is to make you familiar with the usage of the R software for future research projects.
In case of any inquiries, please write me an email to benjamin.mayer(at)uni-ulm.de.
ONLINE CONFERENCE ROOM
Please join on July 30th, 6pm-7pm, via the following Zoom link:
uni-ulm.zoom-x.de/j/65873775152
Meeting-ID: 658 7377 5152
Kenncode: 21747723
STATISTICAL DATA ANALYSIS: AN INTRODUCTION TO R and RSTUDIO
This course will introduce the practical use of the R software for statistical computing (www.r-project.org), and in particular how the RStudio environment is efficiently used.
Using RStudio requires to download both the R software and RStudio, and it is important to download and install the R software first. Under cran.rstudio.com you can select the appropriate download file according to your operating system (Windows, macOS, Linux). Having installed R, the download file for RStudio can be found at https://posit.co/download/rstudio-desktop/.
An installation video (here: for Windows users) can be found here:
https://www.youtube.com/watch?v=TFGYlKvQEQ4
WORKING WITH RSTUDIO: AN INTRODUCTION
An introduction to R
Data management in R
Descriptive statistics in R
Graphical approaches in R
Bivariate statistics in R
Hypothesis testing in R
WORKING WITH RSTUDIO: EXERCISES
Exercise sheets
Exercise: data management in R
Exercise: descriptive statistics in R
Exercise: graphics in R
Exercise: bivariate statistics in R
Exercise: hypothesis testing in R
Solutions (R code)
Solution: data management in R
Solution: descriptive statistics in R
Solution: graphics in R
Solution: bivariate statistics in R
Solution: hypothesis testing in R
Solution: full example R code for analysing the "colon" data set
DATA SETS