Because humans are complex, the questions that are asked and the data that are gathered are also complex. For decades social scientists have gathered data by using surveys, interviews, observations, and experiments. The resulting data reflected choices within the control of the researcher. Now, data are increasingly being generated without any researcher intervention. Our world is full of data coming from multiple types of devices, interaction with applications on these devices, digitized documents, and much more.
The Quantitative Methods in the Social Sciences (QMSS) program seeks to unite Michigan’s excellence in social science with the current revolution in the data science. The minor in Quantitative Methods in the Social Sciences will train the next generation of social scientists in the methods needed to harness all types of quantitative data in order to generate new insights and solutions to the problems of today and tomorrow. The QMSS community is relatively small and tight-knit which fosters a collaborative learning environment. Students in the program work closely with professors and there are ample opportunities for involvement in the program. Students can work as peer mentors or contribute to the student-run blog.
How QMSS is different:
A minor in QMSS will deepen the knowledge and skills for a broadly diverse group of students to work in the rapidly changing environment of the analysis of human data. Existing programs focus on computational methods, big data, data management etc. While QMSS is acutely aware of the need for skills in those domains, the foundational courses focus on a) social science applications (understanding human behavior and beliefs through data analysis, solving societal problems) and b) the particular strengths and needs of students in the social sciences, who often select a topic area (inequality) or discipline (psychology) rather than a methodology or a particular mathematical skillset when they select their major.
Benefit to all students:
Further, students interested in social science research are often asked to take long lists of prerequisites with content they won't need before they can take the "useful" courses that exist in computer science and related disciplines. To teach these methods for social science students, QMSS has flipped the curriculum so that students are learning material relevant to them and this material is connected to their interests. This leads to increased engagement with the curriculum, and a strong understanding of its application to the real world - and their future job prospects. Likewise, the QMSS minor will benefit students with advanced technical and mathematical skills who are interested in majors in the social sciences and need courses like these to help them reason through the application of their tools to social questions.
Skills students learn:
The quantitative skills students will learn in the foundational courses for this minor will be tied to training in social science theories and understandings of crucial ethical issues in data collection and analysis. This training will position students to become leaders and critical thinkers in an era when narrowly trained coders are facing increasing difficulties in navigating the complex interactions among public and private entities. Students who choose this minor will know how to leverage existing models and knowledge with cutting-edge data analytic techniques to develop new breakthroughs in our understanding of the social world. Students will be exposed to R, Python, Tableau, and Excel.
More information about the courses offered can be found on the curriculum tab.
Also, please check out our student-run QMSS blog, Putting Methods to the Madness. If you're interested in contributing, please email firstname.lastname@example.org