Basic R-Course in the Life Sciences

TitleTimeRoomTeacher
Basic R-Course Kickoff08.04.2024 11:00 - 11:30 (Mon)OnlineDaniela Keller
Basic R-Course Q&A115.04.2024 11:00 - 12:30 (Mon)OnlineDaniela Keller
Basic R-Course Q&A222.04.2024 11:00 - 12:30 (Mon)OnlineDaniela Keller
Basic R-Course Q&A329.04.2024 11:00 - 12:30 (Mon)OnlineDaniela Keller
Keywords: 
Statistics, R und RStudio, Data Analysis, Significance Tests, Graphics
Course Description: 

In this course you will learn to use R and Rstudio for doing statistical analysis. You will get to know the most important statistical methods, you will learn how to choose the right method for different situations and use R and Rstudio for analyzing example data with these methods. 

The course will cover the following main topics:

  • Introduction to R and Rstudio
  • General introduction to statistics
  • Descriptive statistics and graphics
  • Normal distribution
  • Significance tests
  • Investigation of dependencies and differences
  • Post-Hoc-Tests
  • Factorial ANOVAs
  • Linear and logistic regression

After the course you will

  • have lost the fear of using R 
  • have learned the basic function of R
  • know how to import and export raw data in R
  • be able to create a descriptive and graphical overview of a data set
  • be able to choose the appropriate significance test or statistical model for an available data set and research question
  • be able to conduct this analysis in R and interpret the results

The course is organized with self-learning material (short videos, handout, example data and exercises) and three live and online Q&A sessions. After a short kick-off meeting you watch the videos and do the exercises at your own pace. Within an interval of one week we meet for three Q&A sessions online, where you can ask questions concerning the topics and exercises of the course or your own projects.

Course aims: 
  • losing the fear of using R
  • learning the basic functionality of R
  • knowing how to handle data in R
  • being able to create a descriptive and graphical overview of a data set
  • being able to choose the appropriate significance test or statistical model
  • be able to conduct statistical analysis in R and interpret the results
Teaching methods: 

Presentation of statistical background, Software tutorials, Examples, Exercises for self study, Q&A sessions, Quiz

This course fits doctoral candidates in the following phase: 

☒ Beginn der Promotion / Beginning of the doctorate
☒ Während der Promotion / During the doctorate
☒ Endphase der Promotion / End of the doctorate

Technical requirements: 

PC, laptop with R and RStudio installed (open source); internet access

Additional information: 

Flipped classroom format. Participants must allow time for independent viewing of the videos and the exercises.

Category: 
Fachspezifische Veranstaltung
Event type: 
Seminar/Workshop
Organizer: 
Graduate Center of Life Sciences
Responsibility for event: 
Hauptverantwortung
Format: 
Digital/Online
Course Language: 
EN
Course Capacity (Max): 
15
Course capacity (Min): 
5
Duration in hours: 
5
Trainer: 
Daniela Keller