MAPSS-QMSA | Master of Arts Program in the Social Sciences

Quantitative Methods and Social Analysis (QMSA) is a one-year program with 9 graduate-level courses over three academic quarters, culminating in an article-length MA thesis. Students in QMSA receive rigorous training in statistical theory and gain critical exposure to the latest quantitative techniques to solve real-world problems. More information about the MAPSS-QMSA concentration can be found here on the Committee on Quantitative Methods in Social, Behavioral, and Health Sciences website.

The QMSA Concentration requires students to complete courses in statistical theory and advanced quantitative methods, from an approved list. In addition, students select three graduate electives in their social science field, participate in the biweekly QMEHSS Quantitative Methods Workshop, and write an MA thesis with a member of the QMSA-affiliated faculty. Questions about the MAPSS-QMSA concentration should be directed to:

Yanyan Sheng, Senior Instructional Professor
Committee on Quantitative Methods
1155 E. 60th Street Chicago, IL 60637
Email: y.sheng@uchicago.edu
Phone: 773-702-0543

QMSA Admissions

Applicants who declare an interest in QMSA must have a minimum quantitative GRE score in the 75th percentile. Applicants must list up to five prior courses in the social sciences, and up to five prior courses in mathematics, statistics, or quantitative methods. They should have prior exposure to calculus and linear algebra. They must furnish a statement of purpose indicating a domain of substantive interest in the social or behavioral sciences, outlining their intended research, and naming two QMSA-affiliated faculty members with whom they wish to work.

Students admitted to other MAPSS concentrations may petition to change their track to QMSA after accepting their offer. Those students must have a minimum quantitative GRE score in the 75th percentile OR qualified transcripts that show successful performance in calculus, linear algebra, and post-introductory statistics courses. Information on the petition process will be sent to all students in early May.

International students on F-1 or J-1 student visas who complete the Master of Arts Program in the Social Sciences (MAPSS) with this concentration may be eligible for employment benefits associated with their respective visa type. The MAPSS-QMSA Concentration is listed as a STEM designated degree by the U.S. Department of Homeland Security for the purposes of the STEM OPT extension allowing eligible students to apply. However, approval for STEM OPT is at the discretion of U.S. Citizenship & Immigration Services. To learn more visit our Office of International Affairs website.

QMSA Program Requirements

QMSA students are required to attend an intensive math camp in September – MACS 33000: Computational Math and Statistics – for a review of linear algebra, differential/integral calculus, probability, and statistical theory that constitute the mathematical foundations of quantitative research methods. QMSA students must take a math/statistics placement exam before or during the orientation week.

The result of this exam and a student’s prior coursework will jointly determine the sequence of courses that the student will take to meet the curricular requirement in statistical theory.

A sequence of two courses in statistical theory is required for all students in the QMSA concentration. To fulfill this requirement, each QMSA student is advised by the Senior Instructional Professor to choose one of the following three series according to his or her preparation and placement exam result.

Beginning Series: Students who have not taken probability and statistics in their prior coursework, or who need to develop a better command of the mathematical foundations of statistical theory, will take SOSC 36006 (Foundations for Statistical Theory) in the Fall Quarter and STAT 24400 (Statistical Theory and Methods I) in the Winter Quarter.

Intermediate Series: Other QMSA students will take STAT 24400 (Statistical Theory and Methods I) in the Fall or Winter) quarter and STAT 24500 (Statistical Theory and Methods II) in the Winter or (Spring) quarter.

Advanced Series: Those with particularly strong mathematics and statistics backgrounds may, in consultation with their faculty mentor or QMSA Senior Instructional Professor, take BUSN 41901 (Probability and Statistics) and BUSN 41902 (Inference in Econometrics and Statistics) to satisfy these course requirements. This sequence of PhD-level courses provides a thorough introduction to classical and Bayesian statistical theory, and offers the necessary tools for many of the advanced courses in the Chicago Booth curriculum.

QMSA students must take MAPS 30000: Perspectives in Social Science Analysis in the Fall and SOSC 36007: Overview of Quantitative Methods in the Social and Behavioral Sciences in the Winter.

The former provides an orientation to major theoretical perspectives that have influenced multiple disciplines in the social sciences and guides students through the process of developing a thesis project. The latter offers an overview of a wide range of quantitative methods, reveals their common logic and inherent connections, and provides a gateway to more advanced coursework across the University.

In consultation with their faculty mentors and the QMSA Senior Instructional Professor, students select two advanced methods courses from the wide range of approved courses listed on the QMSA webpage, which is updated quarterly.

Eligible courses must not be at the introductory level or exclusively about learning a software package. They must not be only incidentally about quantitative methods or applications of quantitative methods learned in other courses. Students who hope to take a course not on the QMSA course list must contact the QMSA Senior Instructional Professor before the quarter begins to start a petition process.

In consultation with their faculty mentor and/or MAPSS preceptor, students select up to 3 social science electives that equip them with the theoretical understanding and the empirical knowledge necessary for their MA projects. Eligible courses must introduce students to the literatures surrounding a significant research problem, and they must have a writing component.

A minimum “B” average is required to earn the QMSA concentration. QMSA students who take SOSC 36006: Foundations for Statistical Theory in the Fall must obtain at least a B+ to ensure that they will succeed in STAT 24400: Statistical Theory and Methods I. Up to two elective courses may be taken pass/fail.

Under the supervision of a faculty mentor and the MAPSS preceptor, every QMSA student is required to complete a research article by the end of the academic year that demonstrates the student’s ability to conduct and present rigorous investigations of a significant research question.

QMSA students must attend the biweekly Workshop on Quantitative Methods that meets every other Friday from 10:30-noon. The Workshop invites leading methodologists to present their work and offers an ideal venue for students to get up to speed with the latest developments in quantitative research. In addition, QMSA students are required to attend a pre-workshop session designed to provide scaffolding and prepare them for active participation in the intellectual discourse around the topic of each workshop.

QMSA Course Offerings

SOSC 36006: Foundations for Statistical Theory. This course is designed for graduate and advanced undergraduate students who aim to develop conceptual understanding of the fundamentals of statistical theory underlying a wide array of quantitative research methods. The course introduces students to probability and statistical theory and emphasizes the connection between statistical theory and the routine practice of statistical applications in quantitative research. Students will gain basic understanding of the concepts of joint, marginal, and conditional probability, Bayes rule, probability distributions of random variables, principles of statistical inference, sampling distributions, and estimation strategies. The course can serve as a preparation for mathematical statistics courses such as STAT 244 (Statistical Theory and Methods 1) and as a theoretical foundation for various advanced quantitative methods courses in the social, behavioral, and health sciences. Prerequisites: Basic knowledge of linear algebra and calculus, specifically differentiation and integration, is necessary to understand the material on continuous distributions, multivariate distributions, and functions of random variables.

STAT 24400: Statistical Theory and Methods I. This course is the first quarter of a two-quarter systematic introduction to the principles and techniques of statistics, as well as to practical considerations in the analysis of data, with emphasis on the analysis of experimental data. This course covers tools from probability and the elements of statistical theory. Topics include the definitions of probability and random variables, binomial and other discrete probability distributions, normal and other continuous probability distributions, joint probability distributions and the transformation of random variables, principles of inference (including Bayesian inference), maximum likelihood estimation, hypothesis testing and confidence intervals, likelihood ratio tests, multinomial distributions, and chi-square tests. Examples are drawn from the social, physical, and biological sciences. The coverage of topics in probability is limited and brief, so students who have taken a course in probability find reinforcement rather than redundancy. Prerequisite(s): MATH 19520 or 20000 with a grade of B or better, or MATH 16300 or 20250 or 20300 or 20700 or STAT 24300 or PHYS 22100.

STAT 24500: Statistical Theory and Methods II. This course is the second quarter of a two- quarter systematic introduction to the principles and techniques of statistics, as well as to practical considerations in the analysis of data, with emphasis on the analysis of experimental data. This course continues from STAT 24400 and covers statistical methodology, including the analysis of variance, regression, correlation, and some multivariate analysis. Some principles of data analysis are introduced, and an attempt is made to present the analysis of variance and regression in a unified framework. Statistical software is used. Prerequisite(s): Linear algebra (MATH 19620 or 20250 or STAT 24300 or equivalent) and STAT 24400 or STAT 24410.

BUSN 41901: Probability and Statistics. This is a PhD course that introduces fundamental statistical methods for academic research in business and economics. It covers basic concepts in probability and statistics, including conditional probability, limit theorems, estimation and inference, and linear regression. Prerequisites: Real analysis and linear algebra. BUSN 41901 is cross-listed as STAT 32400.

BUSN 41902: Inference in Econometrics and Statistics. The focus of this course is methods to draw inferences in econometric models. The course covers linear regression models, generalized methods of moments, nonlinear models, and time series models. The majority of the discussion covers frequentist methods focusing on the use of approximations to finite- sample sampling distributions as a means for obtaining inference. It covers methods that are appropriate for independent data as well as dependent data. We will discuss intuition for how and when to use the econometric tools developed in the class in addition to deriving some of the relevant theoretical properties. Three recommended texts are Econometrics by Hayashi, Econometric Analysis of Cross Section and Panel Data by Wooldridge, and Time Series Analysis by Hamilton. Asymptotic Theory for Econometricians (revised edition) by White provides a useful and concise reference on asymptotic results. Prerequisites: BUSN 41901.

MAPS 30000: Perspectives in Social Science Analysis. This course is an introduction to interdisciplinary social theory which aims to teach students how to read social science research at the graduate level and develop their ability to formulate and execute a successful master’s thesis. It is required of all MAPSS students, regardless of concentration.

SOSC 36007: Overview of Quantitative Methods in the Social and Behavioral Sciences. The course is designed to offer an overview of and present the common logic underlying a wide range of methods developed for rigorous quantitative inquiry in the social and behavioral sciences. Students will become familiar with various research designs, measurement, and advanced analytic strategies broadly applicable to theory-driven and data-informed quantitative research in many disciplines. Moreover, they will understand the inherent connections between different statistical methods, and will become aware of the strengths and limitations of each. In addition, this course will provide a gateway to the numerous offerings of advanced quantitative methods courses. It is suitable for undergraduate and graduate students at any stage of their respective programs. Prerequisite: Introductory level statistics.

See https://voices.uchicago.edu/qrmeth/mapss-qmsa/ for the most updated list of approved courses in advanced quantitative methods. Final course selections must be approved by the QMSA Senior Instructional Professor.