Daniel Schwartz, PhD student in Biostatistics, Department of Public Health Sciences
“I find it so exciting to work on quantitative methods because, when used well, not only can they be crucial to rigorously solving key problems in our fields, but they can also inspire us to pose interesting new questions. UChicago has been a very rich environment for me to “grow up” as a statistician and quantitative researcher because there are so may quantitatively-minded faculty and projects across the University, ranging from the quite theoretical to quite applied. The Quantitative Methods Workshop, in particular, which exposes researchers to methodological problems in sometimes unfamiliar disciplines, has been a real highlight of my time here.”
Xu Qin, PhD in Quantitative Methods in Education and Human Development, Department of Comparative Human Development (winner of a 2019 American Educational Division D Outstanding Dissertation Award; Assistant Professor of Research Methodology, Department of Psychology in Education, University of Pittsburgh)
“I feel very lucky that I pursued my Ph.D. under the guidance of several faculty members in the program. A very unique strength of this program is that faculty members in the program are world-class experts not only in quantitative methods but also in substantive areas. While statisticians spend most of the time developing statistical tools, their inspirations come from real problems and their ultimate goal is to solve real problems. Throughout my doctoral training, I learned how to think about statistical issues from a substantive perspective. This helped to ease my understanding of statistics and stimulate my creative thinking. I believe incoming students will benefit a lot from the interdisciplinary training in the program, just as I did.”
Jiebiao Wang, PhD in Biostatistics, Department of Public Health Sciences (postdoctoral researcher, Department of Statistics and Data Science, Carnegie Mellon University; Assistant Professor of Biostatistics, University of Pittsburgh
“Quantitative Methods lay the foundation for science since they provide evidence a scientific theory. They become even more appealing in the era of big data and artificial intelligence. The University of Chicago has a strong capacity for quantitative methods. There are many faculty members with expertise in statistical theory, methodology development, and applications. It spans a whole spectrum of statistical methods and applications, ranging from social sciences to natural sciences. Students will not only learn statistical methods but will also acquire the ability to find or develop an appropriate method to solve a specific scientific problem. The Quantitative Methods workshop is diverse since the topics arise from different substantive areas, but it is also very coherent because all the topics are under the umbrella of statistical methods. It is an excellent complement to the more theoretical seminars in the Statistics department and more applied workshop in other related departments.”
Jacy R. Anthis, PhD Student in Sociology (Department of Sociology), Econometrics and Statistics (Booth)
“I think the history of 21st century social science will be marked by the enrichment of social theory with computational and analytical sophistication, such as many-dimensional embeddings of social structures and causal identification of social processes. We are coming to realize that all meaningful knowledge can be cashed out in more accurate predictions about observable future events. The training at University of Chicago, particularly the AQM program, has given me an extensive, diverse set of tools for making such advances, and I think many more students would benefit from the workshops, courses, and mentorship of the QMSBHS faculty. This has been instrumental in my own research on the meteoric rise of artificial intelligence (AI) and ensuring these systems are safe and beneficial.”
