Resources

Here is a non exhaustive list of resources and links we find useful. These cover various topics and most are openly available online. We expect you to be creative and search (not only) through these resources if you get stuck with your project or find any topics difficult to understand. If you find it hard to get access to any of the articles or books mentioned here, do not hesitate contacting us. Definitely do not use websites like Sci-Hub or Library Genesis that seem to provide scientific knowledge to all.

Quantitative and digital archaeology

Carlson, D. L. 2017: Quantitative Methods in Archaeology Using R. Cambridge: Cambridge University Press.
VanPool, TL and Leonard, RD. 2011. Quantitative analysis in archaeology. Chichester: Wiley-Blackwell.
Drennan, R. D. 2010: Statistics for Archaeologists: A common sense approach. New York: Springer.
Baxter, M. 2003: Statistics in Archaeology. London: Wiley.
Fletcher, M., Lock, G. R. 1994: Digging Numbers: Elementary statistics for archaeologists. Oxford: Oxbow.
Shennan, S. 1988: Quantifying Archaeology. Edinburgh: Edinburgh University Press.

R programming language and environment

R for Data Science by Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund (2nd Ed.).
Data Visualization. A practical introduction by Kieran Healy.
CRAN Task View is a list of R packages useful in archaeology maintained by Ben Marwick. There is also a list of articles using R in the analysis with data and code published.

Where to look for help

Posit/RStudio cheatsheets, especially data visualization, transformation, tidying and import cheatsheets will come in useful.
Search through Stack Overflow. Find some tips on asking good questions and providing minimal reproducible examples in this thread.

Data visualizations

Choosing proper graph for the data and message you want to communicate can be difficult, have a look at some of galeries of various graphs: Visual vocabulary by Financial Times, From Data to Viz website or The Data Visualisation Catalogue.
Or go for sites with graphs created in R directly (with code): R Graph Gallery or R Charts.
Choosing right colors for your graphs and maps can be difficult, have a look at the Color Brewer website that offers many great color palettes.

Reproducibility

Marwick, B. 2017: Computational Reproducibility in Archaeological Research: Basic Principles and a Case Study of Their Implementation. Journal of Archaeological Method and Theory 24(2): 424–450. DOI: 10.1007/s10816-015-9272-9.
Marwick, B., Boettiger, C. and Mullen, L. 2018: Packaging Data Analytical Work Reproducibly Using R (and Friends). The American Statistician 72(1): 80–88. DOI: 10.1080/00031305.2017.1375986.

Data management

Karl Broman’s guide on how to organize data in spreadsheets. The same as an article, DOI: https://doi.org/gdz6cm.
Jenny Bryan’s slides on naming things.
Hadley Wickham’s paper on tidy data, DOI: https://doi.org/10.18637/jss.v059.i10.

RMarkdown/Quarto and scientific writing

British Ecological Society has a nice series of Guides to Better Science covering various topics including Reproducible Code and Data Management.
A short guide by Ben Marwick on how to setup Atom (this could be any text editor) and Zotero (citation management software).
The Plain Person’s Guide to Plain Text Social Science by Kieran Healy.

R as a GIS and spatial analysis

Geocomputation with R book by Robin Lovelace, Jakub Nowosad, and Jannes Muenchow.
Spatial Data Science book by Edzer Pebesma and Roger Bivand.

Installing R and RStudio

There is a comprehensive guide on how to install R and RStudio in the Hands-On Programming with R book by Garrett Grolemund.

If you do not want to install R on your machine, there are several online compilers or Posit Cloud.