Interdisciplinary PhD in Social & Engineering Systems and Statistics
Requirements:
Students must complete their primary program’s degree requirements along with the IDPS requirements. Statistics requirements must not unreasonably impact performance or progress in a student’s primary degree program.
Grade Requirements: B+ in all required courses (see options below)
PhD Earned on Completion: Social and Engineering Systems and Statistics
IDPS/SES Chair: Ali Jadbabaie
Seminar  
IDS.190  Doctoral Seminar in Statistics 
Probability (pick one)  
6.7700 (6.436)  Fundamentals of Probability 
18.675  Theory of Probability 
Statistics (pick one) 

18.655  Mathematical Statistics 
18.6501  Fundamentals of Statistics 
IDS.160  Mathematical Statistics – a NonAsymptotic Approach 
Computation & Statistics (pick one)  
6.7220 (6.252/15.084)  Nonlinear Optimization 
6.7810 (6.438)  Algorithms for Inference 
6.7900 (6.867)  Machine Learning 
9.520  Statistical Learning Theory and Applications 
14.380/14.381  Statistical Methods in Economics/Estimation and Inference for Linear Causal and Structural Models 
14.382  Econometrics 
15.077  Statistical Learning and Data Mining 
16.391  Statistics for Engineers and Scientists 
17.802  Quantitative Research Methods II: Casual Inference 
17.804  Quantitative Research Methods III: Generalized Linear Models and Extensions 
17.806  Quantitative Research Methods IV: Advanced Topics 
Data Analysis (pick one)  
6.8300 (6.869)  Advances in Computer Vision 
9.073/HST.460  Statistics for Neuroscience Research 
9.272/HST.576  Topics in Neural Signal Processing 
6.8800 (6.555, 16.456/HST.582)  Biomedical Signal and Image Processing 
18.367  Waves and Imaging 
6.3732 (IDS.131/6.439)  Statistics, Computation and Applications 
IDS.957  Practical Experience in Data Analysis 
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