Quantitative skills for archaeological and evolutionary scientists

This course will provide students with training in quantitative methods that form the basis of research across a diverse range of research specialisations. In the first half of the course, students will engage with topics and theoretical debates that form a key part of the archaeological scientist's skillset in the 21st century: principles of good data visualisation, the role of Open Science in fighting the reproducibility crisis, the benefits of meta-analyses for synthesizing previously published datasets, and the reliable application of descriptive and inferential statistical tools in archaeological and evolutionary research. In the second half of the course, the students will apply these skills to gain hands-on experience in computational analysis of datasets from bioarchaeology, evolutionary morphology, zooarchaeology, archaeobotany, stable isotope analysis, organic residue analysis, and palaeogenetics. After completion of the course, students will have a working knowledge of the programs R and jamovi for using descriptive and inferential statistical tools, adapting reproducible code from the literature, experimenting with different approaches for data visualisation, and carrying out large and small meta-analyses. They will be able to present the results in ways that are consistent with science-wide calls for statistical reform and avoiding common misuses of significance testing.