Quantitative Methods in Anthropology


This course is designed as an introduction to quantitative methods used in anthropology. It assumes no statistical or computer background and requires only basic mathematics. The emphasis will be on quantitative analysis as an anthropological research tool, not on probability or statistical theory, although these will be discussed. Students will be taught basic use of the R coding language for class analyses.

Primary Teaching and Learning Goals

  1. Learn useful statistical concepts and issues including variable scales, concepts of independence and dependence, the value and limitations of sampling, measurement error, useful measures of central tendency and dispersion, and accuracy, bias and validity
  2. Learn the difference between description and inference, and how to judge whether an inference is likely to be valid or invalid
  3. Gain familiarity of common parametric and non-parametric statistical tests used in hypothesis testing, the assumptions that underlie their use and how to select potentially appropriate tests given a particular data set and question 
  4. Learn techniques for evaluating assumptions regarding statistical properties of data and be able to assess whether assumptions for statistical tests used have been met, at least approximately; learn, too, what steps may be taken if assumptions are not met 
  5. Practice working with data using the R coding language
  6. Find, read and integrate theoretical and practical information related to one of several possible anthropological issues
  7. Use your quantitative learning to evaluate others’ research, and develop and evaluate your own


Coursework only

Availability 2022

Not taught in 2022



Recommended Reading

Kabacoff R., 2015. R in Action: data analysis and graphics with R, 2nd ed. (ebook available through library)

IDRE (Institute for Digital Research and Teaching):


Coursework only


ANTHRO 309: 15 points


ANTHRO 200 or 201 or 203 or 120 points passed