![]() Note that the workshop focuses on the fundamentals of working with R and data, it will not cover statistical analyses in R.ĭuring the workshop, we will work with RStudio and R Markdown. Finally, you will explore the basics of data visualisation. In the second half of the workshop, you will learn techniques for working with datasets using the ‘tidyverse’ package such as importing data, subsetting and mutating data, performing transformations, and ensuring tidy data principles. Additionally, you will delve into programming techniques such as if statements, loops, and functions. In the first half of the workshop, you will become familiar with R syntax and data types, learn about vectors and data structures, explore handling missing data, and apply indexing techniques for vectors, lists, and dataframes. This one-day workshop will take you from the very basics of R syntax to data handling and visualisation using the ‘tidyverse’ package in R. In this workshop, we aim to give you the tools to start exploring R and all it has to offer for your research. R is a powerful programming language suitable for data handling, visualisation, and statistical analysis. Writing Reproducible Manuscripts in R and Python.Walk-In Hours Research Data and Software.Best Practices in Writing Reproducible Code.Introduction to R & Data for Humanities. ![]() ![]() Learn to write your DMP (online training).Transcription of audio data Close submenu +.The research data repository DataverseNL.Storing and managing data Close submenu +.Policies, codes of conduct and laws Close submenu +.Working safely with research data from home.
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