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GPDI515 - Data Science & Communication with R

Do you have data you'd like to analyze? Would you like to gain insights from your data and communicate them with eye-catching visualizations and reports? Are you tired of being chained to Excel or expensive proprietary software? If the answer to any of these questions is "Yes!", than this workshop is for you. R is an open source and versatile programming language that's perfect for data analysis, visualization, and science communication.

In this all-in-one course, you'll learn the basics of programming and be introduced to the RStudio interface. We'll then move on to how to import and clean data, how to make publication quality plots and visualizations, and how to generate scientific reports to communicate your findings; all within the R ecosystem!

In this three-part interactive workshop, you'll learn to:
• Import CSV and Excel files
• Install and use external packages
• Clean and explore data
• Generate descriptive statistics
• Create and customize plots
• Write custom functions

All of this is done with principles of reproducibility in mind, so you can write code that is clear and easily shareable with others. No previous coding experience is necessary. R is used in fields ranging from linguistics and marketing to ecology and sports analytics and many more. If you want the ability to get more out of your data, join us to get started using R.

IMPORTANT NOTES
1. This workshop is replacing "Beginners Guide to R" and "Reproducible Scientific Analysis with R" from previous semesters as an all-in-one resource for R programming. Those who have taken one of these workshops in the past will find some of the content repetitive.
2. This is a hands-on workshop requiring R and RStudio. Participants require their own computer to complete mandatory activities. Registered participants will receive R and RStudio installation instructions by email a couple days prior to the first meeting.


Learning Objectives


In this workshop, participants will:

1. Discover the terminology of basic coding, such as working directory, script, library, function, csv, concatenation, data frame, etc.;
2. Learn about coding and the types of resources available while coding;
3. Install different R packages;
4. Use vectors and data frames to store and manipulate data;
5. Create projects in R;
6. Familiarize themselves with R and RStudio capabilities that they can apply to their own research


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.

Schedule

Section 1
September 29 - October 13, 2021, 13:00 - 15:00, Wed
Section 2
October 30 - November 13, 2021, 10:00 - 12:00, Sat

Disclaimer: Available spots is an estimation.
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