Prerequisites:

• Basic statistical knowledge
• Basic proficiency in R programming

Who should enroll:

• Students who are struggling with planning and performing the statistical analysis at their doctoral work
• Scientists who want to have statistical advice in a particular project and/or a support in their R programming

Concept of the course:

The proposed course aims to provide personalized support for students struggling with statistical analysis and R programming during their doctoral thesis writing. Through a series of 8 meetings held every Monday, small groups of 6 students will have the opportunity to address their individual questions and challenges related to statistics and R programming in their projects.

Led by an experienced instructor, these sessions will offer individual tailored guidance, hands-on assistance, and practical insights to help students improve their understanding and proficiency in both statistical concepts and the use of the R programming language as well as to help in their own projects. By offering this personalized format, the course seeks to empower students with the tools and confidence needed to succeed in their doctoral thesis.

• Do you have to do statistical analysis in your project, but do not know how to start?
• Do you have to perform a method that you do not understand?
• Do you want to perform your statistical analysis in R but do not know how?

We will discuss your questions and will try to find a solution together!

Other:

The program should be installed on participants’ own laptops:

• R: https://cran.uni-muenster.de/
• RStudio: https://rstudio.com/products/rstudio/download/
• MS Teams: https://www.microsoft.com/en/microsoft-teams/download-app

Trainer:

Dr. Katherine Ogurtsova (Katherine.Ogurtsova@hhu.de) is working in the Institute of Occupational and Social Medicine, in the working group of Environmental Epidemiology, at University Clinic in the Heinrich Heine University. Her primary qualification includes statistical methods in medicine, epidemiology, and public health with the main focus on R-programming and methodological issues.