Graduate Certificate in Quantitative Data Analysis

Outstanding abilities and knowledge in quantitative analysis, methods and interpretation is a key skill for scholars in a wide range of disciplines within the social sciences. Further, many of the important practical, analytical and conceptual skills are shared across disciplines. Many of the graduate programs in the social sciences include basic quantitative analysis skills within their core required curriculum, but many students would benefit from advanced training in this domain. Such advanced training would benefit the development of their research programs and their ability to apply their skills in a wide variety of occupational domains. This certificate program would provide an organized way for students to achieve an advanced level of knowledge and skill in quantitative social science data analysis, interpretation and visualization. The certificate would require students to master both an introductory level of quantitative skills and knowledge, as well as more advanced quantitative skills and knowledge. Some of the introductory level course might overlap with courses that are already required within a student’s individual Ph.D. program curriculum, but the advanced level would require them to go beyond the basic expectations of their graduate program in order to achieve greater depth and breadth of knowledge and abilities. This Certificate is open to students enrolled in Ph.D. programs in the Arts & Sciences Social Science Departments, including the Ph.D. programs in Psychological & Brain Sciences, Economics, Anthropology, and Education.

*Students in Political Science are not eligible for this certificate

Programming Requirements

The ability to satisfactorily complete the courses required in this certificate will require that students have at least entry level programming skills in languages such as “R” or python or MATLAB. Formal training in one or more of these languages is not a part of this certificate. However, students who do not have such skills are encouraged to pursue the array of opportunities to gain such skills that are available at Washington University. This includes summer courses or “boot camps” in R or python offered in departments such as Psychological & Brain Sciences, or Public Health (e.g., M19-513, Division of Public Health Sciences Biostat R Primer) or the range of courses offered within the Computer Science department (many are at the undergraduate level, but would serve allow graduate students to develop usable programming skills). Students in Political Science are not eligible for this certificate

Certificate Requirements

The goal of the Certificate is to ensure that students have both a solid basis in Probability and Statistics as well as Inference and Quantitative Research Design, as well as some depth of experience in a more advanced topic area. As such, students completing the Certificate are required to take at least five courses. At least one course must be from the Probability and Statistics group of courses outlined below and at least one course must be from the Inference and Quantitative Research Design group of courses. In addition, students must take at least two courses from one of the three focus areas (Longitudinal and Time Series Data Analysis, Multivariate and Machine Learning Analysis, Data Mining and Specialized Research Tools), with both courses in the same focus area. The fifth course can be from any of the three focus areas or can be a second course from the Probability and Statistics group. Of note, some courses appear in more than one area, but a course can only be used to fill one of the requirements. In consultation with the certificate advisor, students may substitute equivalent coursework or more demanding mathematical treatments of the same course material. This Certificate is open to students enrolled in Ph.D. programs in the Arts & Sciences Social Science Departments, including the Ph.D. programs in Psychological & Brain Sciences, Economics, Anthropology, and Education. Students in Political Science are not eligible for this certificate

In addition, students can achieve credit for one of the courses listed below if they serve as the Assistant to the Instructor or Instructor in that class. Students should consult with Deanna Barch about the process for doing so, which involves signing up for a 3 credit “readings” graduate course in psychology (Psych 560/561).

Probability and Statistics (at least one)

L40 SOC 5050 Quantitative Methods I
L40 SOC 5051 Quantitative Methods II
L33 5066 Quantitative Methods I
L33 5067 Quantitative Methods II
S50 5230 Applied Linear Modeling
L32 581 Quantitative Methods I
L32 582 Quantitative Methods II
L48 5365 Problems in Applied Data Analysis
L32 572 Quantitative Methods in Pol Analysis II: Linear Models (Generalized Linear Models)
L11 508 Mathematics for Economics (Probability and Statistics Review)
S90 6900 Applied Linear Regression Analysis

Inference and Quantitative Research Design (at least one, but no more than one for certificate)

L40 SOC 5200 Research Design
L32 5024 Causal Inference
L33 5011 Research Designs and Methods
L12 503 Foundations of Educational Research
L24 420 Experimental Design (with graduate extension)
L12 519 Principles and Methods of Quantitative Educational Research

Longitudinal and Time-Series Data Analysis

S90 6600 Multilevel and Longitudinal Modeling
S90 6905 Propensity Score Analysis
L33 5068 Hierarchical Linear Models
B54 661 Analysis of Time Series Data
M21 618 Survival Analysis
L32 584 Multilevel Models in Quantitative Research
L33 5165 Applied Longitudinal Data Analysis
S90 6901 SEM class in the Brown School

Multivariate and Machine Learning Analysis

L33 5012 Selected Topics in Design and Statistics
L33 516 Applied Multivariate Analysis
E81 517A Machine Learning
L24 535 Topics in Combinatorics
E81 514A Data Mining
L24 470 Graph Theory (with graduate extension)
S90 6901 Structural Equation Modeling
S90 6901 SEM class in the Brown School

Data Mining and Specialized Research Tools

L33 5167 Applied Bayesian Statistics for Psychologists
S65 5082 Foundations of Geographic Information System (GIS) for the Applied Social Sciences
E81 514A Data Mining
E81 517A Machine Learning
M21 550 Introduction to Bioinformatics
L24 459 Bayesian Statistics (with graduate extension)
E81 316 Social Network Analysis (with graduate extension)
S90 SWDT 5010 Social Network Analysis
L11 5161 Applied Econometrics

How to Apply

Students interested in the Graduate Certificate in Quantitative Data Analysis should first apply for admission to the Washington University department in which they wish to obtain an advanced degree. After being admitted, each student should notify his/her department advisor and the Certificate Program director (Deanna Barch; dbarch@wustl.edu) of plans to obtain Certificate. Second, students should submit an "Application for Admission to Certificate Program" form (click on Certificate Program and then on Application) to the Office of Graduate Studies in Arts and Sciences office, with a copy to the Graduate Certificate in Quantitative Data Analysis office.