This course provides training for interdisciplinary scholars to analyze big data to have social impact. Students will receive real-world instruction in data analytics from faculty through case studies across the fields of health, social services, business, and psychology. This course is about acquiring new skills in data analytics as well as the application and synthesis of skills obtained across disciplines to tackle complex problems through a social justice lens. Using a team science approach, interdisciplinary groups of students will develop their own research question, link datasets through geographic identifiers, analyze data using quantitative skills and mixed methods techniques, and generate outputs with impact. Training will be provided on how to produce outputs for and present results to a range of audiences.
The overarching aim of the course is to provide students with hands-on opportunities to use data analytics to address pressing social problems from interdisciplinary perspectives. A recurring theme will be on the ethical implications of big data and how to design research questions that expose and mitigate social inequities.
Prerequisites: At least one semester, but preferably one year, of graduate-level statistics, with experience in regression analysis. Stata statistical software will be used in the course.
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