The community behind R is built by inspired scientists that share their tools and knowledge freely to encourage equal access for all aspiring researchers and championing academic integrity. The tools available through R aid in every step of data analysis; including creating experiments, cataloging and organizing data, analyzing the results, and visualizing our findings all in one software environment.
The power of programming also increases the flexibility and automation of these tasks saving an abundance of time and ensuring each step can be accurately reproduced. Often, courses that use the R software to demonstrate statistical concepts face the dual challenge of introducing two distinct and equally intricate topics at once; programming and statistics. In most cases, the focus must be shifted away from programming due to constraints on time and breadth to the potential confusion and dismay (repeated appearance of error messages) of novice learners in statistics.
This workshop aims to provide a solid foundation of programming concepts such that attendees can confidently approach more advanced statistical courses or independently improve their statistical skills. Many of the ideas that will be covered can apply to many different programming languages, despite R being the main tool.
Learning outcomes
- Utilize various variable types and functions to import, manipulate, and visualize real-world data.
- Internalize a preliminary overview of the programming elements and how they can be used in the context of statistical analyses.
- Build on existing knowledge to engage in more advanced statistical courses and/or further independent learning.
Prerequisites
No previous programming experience is required at all. Only a basic understanding of how to use a computer (ex. installing programs, searching the internet, searching files, etc.).
Target audience
Students, PhDs, Postdocs, Researchers, and Technical personnel.
Required Materials
In addition to a laptop, the participant should have installed R Software and Rstudio.