# Anthropology 304: Data Analysis in the Anthropological Sciences

## Description

In this course, we will develop a statistical toolkit appropriate for anthropologists. This will be done by developing the logic of likelihood-based approaches to inference. The emphasis will be on practical data analysis and the development of a problem-solving approach to inference. Students taking the course will gain skills that significantly improve their ability to:

- Read quantitative arguments in an informed, critical way
- Use computers to manage and analyze anthropological data
- Convey quantitative arguments in scholarly publications
- Design research projects to generate data that can be quantitatively analyzed

In addition to the general goal of developing quantitative fluency, we will learn specific statistical tools, chosen to reflect the types of data-analysis problems faced by field anthropologists and biosocial scientists more generally. These include:

- Linear models (linear regression, multiple regression, analysis of variance, linear mixed models)
- Generalized linear models (logistic regression, loglinear models)
- Event-History analysis (hazard models, counting-process models)

This restricted directory holds the various hand-outs (e.g.,
lecture notes, supplementary readings, sample code, etc.) that we will accumulate
throughout the quarter.

This restricted directory holds the readings not contained in the class texts.

This page contains pointers to resources statistical and computational resources relevant for the course.

Another goal of the class is to develop an online reference for data analysis using R for anthropology and the biosocial sciences more generally. This blog will contain examples of worked problems and sample code. Other (non-statistical) examples of quantitative analysis will probably sneak in here as well...

Last Modified: 03.28.2013
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