Introduction to R (Autumn 2024)


48662-01 – Lecture with exercises (2 CP) / Vorlesung mit Übungen (2 KP)

Every Wednesday 10:15 - 12:00

Lectures are taking place in the Biozentrum Neubau, Hörsaal U1.141.

 

No.  Date Teacher Title Code, Datasets
1 18.09.2024 Julien Introduction to scripting, computing and RStudio
2 25.09.2024 Robert Reading in and writing out data penguins.csv, penguins.xlsx, penguins_extra.xlsx, penguins2.csv
3 02.10.2024 Charlotte tidyverse: pipe operator, filter, select, mutate penguins.csv
4 09.10.2024 Florian tidyverse: arrange, slice, group_by and summarize penguins.csv
5 16.10.2024 Michael tidyverse: joins and pivots, introduction to ggplot2 penguins.csv
6 23.10.2024 Charlotte Plotting and visualizing data with ggplot2 penguins.csv, ggplot2 cheat sheet
7 30.10.2024 Robert EXAM 1
8 06.11.2024 Anastasiya Vectorized operations, calling and writing functions
9 13.11.2024 Athimed Writing functions, conditional statements penguins.csv, summarize_values.R
10 20.11.2024 Michal For-loops, apply family of functions Kaggle_mentalHealthDataset.zip, 10_DepressionDataset_analysis.R
11 27.11.2024 Pan Random variables, distributions, descriptive statistics and testing melanoma_data.txt
12 04.12.2024 Michael Statistical modelling, lm
13 11.12.2024 Pan Statistical modelling II: Model selection melanoma_data.txt
14 18.12.2024 Florian EXAM 2

This overview is also available as calendar file (ICS). For further information about the lectures, please contact the corresponding teachers.

Description

  • During the Wednesday session from 10:15 to 12:00, we will go through the lecture material together, present the solutions to the exercises and answer your questions.
  • In case you do not need credit points and would like to still access the course material in ADAM please send an email to one of the teachers to be added to the course workspace.

Exams

  • We will have two exam sessions (both held online) in the form of multiple-answer questions (with one correct answer each). You can receive a maximum of 24 points from both exams together and in order to pass the course successfully you need to get a total of 12 points minimum.

Requirements

There are no prior requirements for the course, except for access to R, see below.

Try running R before attending the course - you may need to set up the language. We recommend to have you R/Rstudio in English. But setting this permanently is platform-dependent:

You should also make sure that you can locate and type out special coding-related characters on your keyboard, such as parentheses (), square brackets [], and curly brackets {}, as these are not always obvious to obtain on all keyboards. It is recommended that you find a dataset of your own to practice with, in addition to the course material.

R installation

It is recommended to have an up-to-date installation of R on your computer (i.e., R version >= 4.4.0, available here).

Together with it, we strongly recommend you install Rstudio too.

If you have limited rights to install software on your computer, please contact your ITs before the course.

If a local installation is not possible on your computer, there is the possibility of using RStudio server, a browser-based interface to a version of R running on a remote server. Here are the different options:

For people with an existing sciCORE account:

  • If not at the University, connect to University VPN using the Global Protect
  • Go to https://ood.scicore.unibas.ch
  • Log in with your Unibas username and password
  • Pick RStudio-Server app
  • Select R version 4.3.0 (or newer), “small” instance (with 4 cores and 26GB of RAM), runtime 6 hours

For FMI members:

  • If not at the FMI, connect to VPN using the Ivanti Secure Access (previously PulseSecure) client
  • Go to http://rstudio.fmi.ch
  • Log in with your FMI username and password

Others: