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BiolPostgrad_Rworkshop2023

This is the material for the "R for Reproducible Research and Data Wrangling"
by Giulia Puntin (me 😉).

Feel free to 📥download, 🐱‍💻play around with it, and 💬get in touch if you have any feedback or comments!

And if you feel like saying thank you ...
Buy Me A Coffee

or endorse my skills on LinkedIn


Description

R for Reproducible data wrangling
What happens before the stats: the power of R Tidyverse for wrangling, cleaning, and exploring your data.

Rationale: Most biologists use R for data analysis and visualization. But most still rely on spreadsheets to go from the raw data to data tables suited for specific uses (e.g., a statistical test or plotting). This makes analysis messy, unnecessarily frustrating, and, most importantly, not reproducible. Here we will learn how to do it all within the same workflow using the powerful and intuitive functions of the Tidyverse (includes ggplot!).

Goal: reproducible research & higher efficiency in data wrangling (& more fun!)

Target audience:

  • R novices
  • R intermediate users that are not familiar with the Tidyverse

This workshop covers:

  • The concept of reproducible research and the importance of always manipulating data through (R) scripts
  • Introduction to the powerful and versatile Tidyverse
  • Working example of R script (+ associated dummy data set) to simulate a data analysis workflow that covers the most useful functions to explore, check, correct, reshape, and visualize biological data

This workshop does NOT cover:

  • Download and installation of R and R Studio
  • Explanation of the basics of the R coding language

Info for attendees

📅 When?

Tuesday, 23 May 2023, 2:00pm-4:30pm

🌏 Where?

50-S201 - Hawken Engineering Building, Collaborative Room, UQ Campus St Lucia, QLD, Australia

💰 Cost?

FREE

🧳 What to bring?

Your own laptop with R, R Studio, and the tidyverse package installed

📜 What to prepare?

Familiarise yourself with the following core concepts of R (no need to become an expert, just don’t be overwhelmed by new terminology):

  • Data structures: vectors, matrices, arrays, data frames, and lists
  • Data types (classes): know that they exist and have a rough understanding of what they mean
  • R functions and R packages

✍🏽 Registration

Please register your interest here (Google form): https://forms.gle/8xBemTQdYdM4beFJ9 Initially opening to the School of Biology first but will extend to others depending on interest (we are limited by room capacity)


Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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