R and Statistics for Archaeologists

Course overview

The teaching materials on this site are intended for teaching Statistics and R programming workshops to archaeologists.

This course follows the tidyverse philosophy of understanding and analysing your data through a repeated cycle of transforming, visualising, and modelling.

Image taken from the R4DS book

Upcoming and past workshops can be found here:

Course modules

The course contains multiple modules that can be used to construct workshops of varying durations and customised to suit the participants’ needs.

Core

The core module contains an introduction to R and RStudio, an example workflow, and data import and cleaning.

Durations are rough estimates.

Component Description Materials Duration
Setup Installation of R and RStudio 00 - Getting Started Unknown
R Basics Basics of the R programming language Code-along: 01 - R Basics Unknown
Example workflow Code-along: 02 - An Example Workflow ~1 hour
Project organisation A brief discussion of how to organise a project with RStudio Projects. Code-along: 03 - Getting Organised
Slides: 01 - RStudio Projects
~10 mins
Cleaning Data Importing and cleaning data from a .xlsx file. Code-along: 04 - Cleaning Data Unknown
Stats basics Basics of statistics Slides: 02 - Stats Basics Unknown

Understand

Component Description Materials Duration
Visualising Data Visualising the cleaned data with ggplot2 Code-along: 05 - Visualising Data ~100 mins
Transforming Data Transforming the cleaned data with dplyr Code-along: 06 - Transforming Data ~120 mins

Communicate

Component Description Materials Duration
Communicating Results Creating a Quarto document to combine narrative and code with output Code-along: 08 - Communicating Results ~90 mins

Extensions

Future work is planned on the following extensions (help needed!):

  • Collaborative coding with Git(Hub)
  • Reproducible Research
  • Topic-specific modules
    • Skeletal age-at-death and sex estimation
    • Radiocarbon dating
    • Dendrochronology
    • etc.

Course outcomes

Understand enough to explore more on your own and be able to solve the issues you run into. Because you will run into issues. Everyone runs into issues. It’s VERY satisfying once you have solved them, though.