Get R_eady

Provider

Epidemiology, Biostatistics and Prevention Institute (Prof. Dr. rer. nat. Ulrike Held)

Get R_eady: Introduction to Data Analysis for Empirical Research

Description

The course offers an introduction to data analysis in the transdisciplinary field of empirical (medical) research in the programming language R. The R system for statistical computing is openly available at https://www.r-project.org and provides a simple and flexible software environment for statistical analyses and graphics. Tailored to the application in empirical research, the course covers the basics of programming and data formats in R, as well as the essential steps of a data analysis including data manipulation, descriptive statistics, statistical tests and graphical representations. Reflections on research methodology and transdisciplinarity are addressed and critical thinking is encouraged.

Target group

Students at Master's or PhD level, involved in empirical or medical research. Some knowledge of biostatistics is an advantage.

Course dates

Friday 14.00 - 17.00

04.03.2022, 11.03.2022, 18.03.2022

The course will be held in English.

Assessment / ECTS Credits

1 ECTS

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Get R_eady: Dynamic Reporting & Reproducibility in Research

Description

Larger collections of data are becoming increasingly available. To exploit their potential, statistical analysis skills are needed. The direct link between data and visualization/reporting of results is highly relevant in all empirical research disciplines, as several scientific fields have recently been criticized for lack of reproducibility.

Dynamic reporting tools can be used to directly link data, visualization and analysis outputs, allowing for rapid adaption after possible changes in the dataset, e.g. after data preparation, validation or in the context of manuscript revision.

Tailored to applications in empirical research, the course covers the basics of dynamic programming in R, including examples of dynamic reports for presentations, manuscripts, and html websites. Research methodology is reflected upon, especially in relation to reproducibility, Open Science and transdisciplinarity. Exemplary reports from different disciplines will be compiled and presented by the students.