Introduction to Statistics in R
Full course description
R is a programming language frequently used in data science and related fields for data processing, data visualization, and statistical analysis. Working with data in R requires writing code, which makes the data processing steps and analysis procedure transparent and reproducible. The core functions of R are being continually expanded by a community of users who write and maintain packages containing more specialist functions, meaning that R is a flexible tool that is adaptable to a very wide range of data types (e.g., questionnaire responses, neurophysiological data), while a broad spectrum of data analysis approaches are catered for.
Designed for users with little or no experience with R, this course will make use of RStudio, an open-source program that facilitates the writing and storage of R code. Students will be introduced to the basic steps of data processing, visualization, and analysis. These procedures will taught and practiced in the context of experimental data. Critically, students will be empowered to troubleshoot their own code, by identifying problems in their code and seeking potential solutions in the documentation or online. Students will thereby be able to begin writing their own code independently.
Course objectives
After completing this course, students will be able to:
- Import and handle data in R
- Create graphs and run basic statistical analyses in R
- Document data analysis output from R