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"Data Literacy: Introduction to R"

Veronika Batzdorfer veronika.batzdorfer@kit.edu


Course description

The open source software package R is free of charge and offers standard data analysis procedures as well as a comprehensive repertoire of highly specialized processes and procedures, even for complex applications. After providing an introduction to the basic concepts and functionalities of R, we will go through a prototypical data analysis workflow in the course: import, wrangling, exploration, (basic) analysis, reporting.

Learning objectives

By the end of the course participants should be:

  • Comfortable with using R and RStudio
  • Able to import, wrangle, and explore their data with R
  • Able to conduct basic visualizations and analyses of their data with R
  • Able to generate reproducible research reports using R Markdown

Course Schedule

Day 1: [07-11]

Day Time Topic
Friday 09:00 - 10:00 Onboarding & Getting Started with R
Friday 10:00 - 10:10 Break
Friday 10:10 - 12:00 Data Types & Loading & Data Wrangling
Friday 12:00 - 13:00 Lunch Break
Friday 13:00 - 14:45 Data Wrangling2 & EDA
Friday 14:45 - 15:00 Break
Friday 15:00 - 16:00 Data Workflows & Github
Friday 16:00 - 16:10 Break
Friday 16:10 - 17:00 Tidy Tuesday -- Group Work

Day 2: [21-11]

Day Time Topic
Friday 09:00 - 10:45 Data Visualisation & Confirmatory Analyses
Friday 10:45 - 11:00 Break
Friday 11:00 - 12:00 Large Language Models & Wikipedia
Friday 12:00 - 13:00 Lunch Break
Friday 13:00 - 14:45 Reproducible Reporting with R Markdown
Friday 14:45 - 15:00 Break
Friday 15:00 - 16:00 Group exploration
Friday 16:00 - 16:10 Break
Friday 16:10 - 17:00 Group pitches & Wrap-up

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