This short course introduces historical archaeologists to R, a programming language and environment for statistical computing. R has many advantages, first and foremost it is free and open source. It is supported by a large community of talented programmers, and has excellent graphics and plotting capabilities.
Led by Peter Alonzi (Assistant Professor, School of Data Science, University of Virginia) and staff from the Monticello Archaeology Department and DAACS, this short course series offers seven two-hour classes aimed at introducing archaeologists to R. The lessons are designed for beginners and assume that participants have no experience with programming.
Each lesson has been recorded and is provided online. Visit the DAACS Open Academy GitHub repository for links to workshop videos, workshop slides, and other resources related to the short course.
Lesson 1: Introduction to R, Part 1
Lesson Description: What is R? Why should we be interested in using it? What are its key parts? In this class, you will learn about the program, why it is ideal for archaeological analysis and data sharing, and learn how to write your first program in R.
Lesson 2: Introduction to R, Part 2
Lesson Description: Building on Part I, participants are introduced to actions, such as how to import a dataset in R. If you have your own digital dataset, we will also give you instructions in this class on how to get it ready for Lesson 7.
Lesson 3: Small Steps with R
Lesson Description: This lesson reinforces key concepts from Lessons 5 and 6 (Introduction to R). Practice your budding R skills with exercises using real archaeological datasets. We walk you through each one, step-by-step.
Lesson 4: Using R to Clean Data
Lesson Description: Learn how to seriate data using R and produce plots by frequency and stratigraphy, and learn how to seriate different analytical groups.
Lesson 5: Mean Ceramic Dates and TPQs in R
Lesson Description: This class teaches students how to calculate Mean Ceramic Dates and TPQs using ceramic ware types. We walk students through the code using a real archaeological dataset. We discuss each step of the program, and show how it can be adapted for use with your own data.
Lesson 6: Calculate and Plot Relative Frequencies and Abundance Indices in R
Lesson Description: This class introduces students to simple calculations in R, including relative frequencies and abundance indices. The work will build off the dataset used in previous lessons.
Lesson 7: Learn Seriation in R
Lesson Description: Learn how to seriate data using R and produce plots by frequency and stratigraphy, and learn how to seriate different analytical groups.
