Scientific Analysis and Presentation of Data

Abstract

This course introduces students to scientific work with data, covering the full workflow from importing datasets (e.g., from Excel) to performing basic statistical analyses and generating clear, scientifically accurate visualizations. Through hands-on exercises in R and RStudio, students gain practical experience in data analysis and the creation of meaningful graphical representations.

Objective

By the end of the course, students will be able to: - describe and apply key statistical methods commonly used in bachelor theses, including descriptive statistics, linear regression, and simple analyses of variance; - import, structure, and analyze data using R and RStudio; - create clear, accurate, and task-appropriate graphical representations of data; - critically assess the suitability and limitations of statistical methods and data visualizations; present data and analytical results in a scientifically sound and audience-appropriate manner.

Content

Tentative Programme: - Introduction - Introduction to 'R' - Data import and graphical presentation - Correct and problematic graphical data displays - Statistical distribution and confidence intervals - Statistical tests - Repetition and hands-on applications - Correlation analysis - Linear regressions - Analysis of Variance Last week of semester: examination (Leistungskontrolle)

Resources