Overview
Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills for free at our R workshops!
The D-Lab's R Fundamentals 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, import, export, manipulate, and visualize data, and learn to write shorthand functions of your code. After completion of this workshop you will have a foundational understanding to create, organize, and utilize workflows for your personal research.
Each of the four parts is divided into a lecture-style format interrupted by short breaks, challenge problems, and discussions. Instructors and TAs are dedicated to engaging you in the classroom and answering questions in plain language. No prior experience or background knowledge is required.
R Fundamentals Part 1: Introduction
Students will learn how to navigate the R Studio environment. You will also learn how to store data, characteristics of basic data types and data structures, the importance of data frames (think Excel spreadsheets), and how to save your work.
R Fundamentals Part 2: Subsetting and Reshaping
Students will 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. Terms like subset, bracket notation, and logical vectors will be defined and reintroduced in Part 2.
R Fundamentals: Part 3
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. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.
R Fundamentals: Part 4:
In the final part, we will review data importation, subsetting, and visualization. Students will then be given the majority of time to reproduce a workflow on two different datasets, ask questions, and dive in-depth to ggplot2.
Be sure to download R, RStudio, and the workshop materials before the workshop:
1. Download R: https://cloud.r-project.org/
2. Download RStudio Desktop Open Source License FREE: https://www.rstudio.com/products/rstudio/download/
3. Download workshop materials: https://github.com/dlab-berkeley/R-Fundamentals
a. Click the green "Clone or Download" button
b. Click "Download zip"
c. Extract this file to your Desktop (Mac users double click; PC users right-click and select "Extract All")
