IDCE30103

Description

Section information text: This course introduces students to advanced analysis of data related to development and interpretation and communication of quantitative data. We begin with an overview of theoretical approaches to data analysis, explore their use, and guide students in applying them to individual projects. We will learn ways of organizing, analyzing, visualizing, and presenting data from publicly available national and international databases. The first half of the semester will include quantitative analytics, visualization, and presentation of health-related data. The second half of the semester will consist of ways of researching mobile, hidden, and vulnerable populations using social network analysis. Social network analysis, not to be confused with social networking, is a specialized methodology that examines the patterns of relationships among individuals, community, countries, etc. to identify who the most important people are in a network, who has the most influence or social capital, sub-groups, and if time permits, "hidden or shadow networks". SNA can also be used to evaluate collaboration, coalition, and partnership networks. This course will assume that students will have basic information/quantitative literacy and are not intimidated by data and numbers. Classroom sessions include lectures, discussions, and lab sessions. Course open to IDCE graduate students; ID seniors or ADP students with previous analytics experience. If space permits, graduate students from other departments may request permission to enroll in the class.