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GPDI515 - Beginner’s Guide to the R Programming Language

Is it time for you to learn how to code? If the answer is “Yes!”, we propose an unconventional way to start: coding with R, which is a free, powerful and simple programming language for data analysis.

In this workshop, you will learn the basics of the R syntax and how it can support your research. Our aim is to put you on a path to start using R for basic data work and to guide you through becoming a self-learner. We will provide you with a list of resources
that can help you get better at coding with R in a self-paced manner.

Throughout the workshop, you will be given short exercises mostly focused on data analysis. These exercises aim to teach you:
- how to write an R script for a small task;
- how to write data into a text file;
- how to read data from a text file;
- how to create and subset a data set;
- how to install and use an R library;
- how to plot a graph.

IMPORTANT NOTE
Participants must bring their own laptops. Before the workshop, they are strongly encouraged to install R (version 3.2.2 or higher) and RStudio on their laptops. Otherwise, a laptop with internet access is enough to follow the exercises in the first session of the workshop.

To learn how to install R and RStudio:
Linux: https://youtu.be/YBOpy1WK-bg
Apple OS: https://youtu.be/GFImMj1lMRI
Windows: https://youtu.be/GAGUDL-4aVw



Learning Objectives


In this workshop, participants will:

1. Discover the terminology of basic coding, such as working directory, compiling a code, script, library, function, csv, concatenation, data frame, etc;
2. Learn about coding and the types of resources they will need while coding;
3. Install different R libraries;
4. Use a minimum of 10 basic built-in functions in R;
5. Use vectors and data frames to store and manipulate data;
6. Write and execute a simple R script.


Leaders Information


This workshop is led by Alexander Albury.
Alex is a PhD student in Psychology working in the Penhune Lab for Motor Learning and Neural Plasticity. He studies how musical complexity and predictability affect how we learn and experience music. Alex is passionate about data science and programming and enjoys learning and sharing new techniques to make science easier and more accessible.

This workshop is not scheduled at this time.
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