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This workshop is a four-part introductory series that will teach you R from scratch with clear introductions, concise examples, and support documents. You will learn how to download and install the open-sourced R Studio software, understand data and basic manipulations, import and subset data, explore and visualize data, and understand the basics of automation in the form of loops and functions. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.
Each of the parts is divided into a lecture-style coding walkthrough interrupted by challenge problems, discussions of the solutions, and breaks. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language.
Learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data, the importance of data frames (think Excel spreadsheets), and how to save your work.
You will then be introduced to loading data from files and various ways to subset it with an emphasis on bracket notation. You will also learn how to use logical vectors, search for and subset missing data, and merge data frames.
Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots using ggplot.
In the final part, we will cover how to use programming control structures such as functions, for-loops, and if-else statements to make more readable and re-usable code.
Prerequisites: None
Workshop Materials: https://github.com/dlab-berkeley/R-Fundamentals(link is external)
Software Requirements: Installation Instructions(link is external) for R and RStudio