Our health and well-being are complex phenomena, influenced by factors at levels ranging from individual genes to political, cultural and economic systems. In this class, we focus on the many ways in which social interactions influence our health both positively and negatively, and vice versa. This has been a particularly active area of research in the last decade in many fields, including anthropology. We will consider why it is important to study such influences, how one might measure them and disentangle their effects, and what the current research has shown. We will also learn how one goes about collecting, organizing, visualizing and analyzing the kinds of data needed to uncover these relationships.
This course has a strong hands-on component. Students will:
- read and dissect complex analyses from the scientific literature
- develop a well-designed survey that obtains egocentric social network data
- visualize and manage egocentric and sociometric data
- conduct basic analyses on egocentric and sociometric data, and their relationships to health outcomes
- articulate limitations and challenges of social network data
- apply concepts of network causality to a range of scenarios
Student will be required to use either Excel or R or both.
The course contains tutorials and labs designed to teach the skills needed for students to succeed at these forms of exploration.