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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, Political Science, Anthropology, and Education.

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, Political Science, 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).

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, Political Science, Anthropology, and Education.

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) 

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) 

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

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 

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 Graduate School of Arts and Sciences office, with a copy to the Graduate Certificate in Quantitative Data Analysis office. In addition, you need to fill out this information form so that we know who is participating in the certificate program. The earlier we know who you are, the earlier we can include you in mailings about Program activities, lectures, conferences, and other events.