Interdisciplinary Doctor of Philosophy in Statistics

Interdisciplinary Doctoral Program in Statistics

Common Core

All students in the Interdisciplinary Doctoral Program in Statistics are required to complete the common core for a total of 27 units.

6.436[J]	Fundamentals of Probability	12
or 18.675	Theory of Probability
IDS.190	Doctoral Seminar in Statistics and Data Science	3
Select one of the following: 1		12
18.6501	Fundamentals of Statistics
18.655	Mathematical Statistics
IDS.160[J]	Mathematical Statistics: a Non-Asymptotic Approach
Total Units		27

1	Mathematics students may not elect 18.6501.

Program-specific Requirements

Each student must complete the requirements specified by their home department in the lists below by taking one subject from the Computation and Statistics category and one subject from the Data Analysis category.

Aeronautics and Astronautics

Computation and Statistics
Select one of the following:		12
6.438	Algorithms for Inference
6.867	Machine Learning
9.520[J]	Statistical Learning Theory and Applications
16.391[J]	Statistics for Engineers and Scientists
16.940	Numerical Methods for Stochastic Modeling and Inference
Data Analysis
Select one of the following:		12
16.393	Statistical Communication and Localization Theory
16.470	Statistical Methods in Experimental Design
IDS.131[J]	Statistics, Computation and Applications
Total Units		24

Brain and Cognitive Sciences

Computation and Statistics
Select one of the following:		12
6.555[J]	Biomedical Signal and Image Processing
6.867	Machine Learning
9.190	Computational Psycholinguistics
9.520[J]	Statistical Learning Theory and Applications
9.660	Computational Cognitive Science
Data Analysis
Select one of the following:		12
9.073[J]	Statistics for Neuroscience Research
9.272[J]	Topics in Neural Signal Processing
9.583[J]	Functional Magnetic Resonance Imaging: Data Acquisition and Analysis
Total Units		24

Economics

Computation and Statistics
Select one of the following: 1		12
9.520[J]	Statistical Learning Theory and Applications
6.867	Machine Learning
Data Analysis
14.192	Advanced Research and Communication	12
14.386	New Econometric Methods	12
or 14.387	Applied Econometrics
Total Units		36

1	Students may substitute a more advanced subject with permission of the program director.

Mathematics

Computation and Statistics
Select one of the following: 1		12
6.252[J]	Nonlinear Optimization
6.256[J]	Algebraic Techniques and Semidefinite Optimization
6.438	Algorithms for Inference
6.867	Machine Learning
9.520[J]	Statistical Learning Theory and Applications
18.337[J]	Parallel Computing and Scientific Machine Learning
18.338	Eigenvalues of Random Matrices
18.415[J]	Advanced Algorithms
18.416[J]	Randomized Algorithms
18.657	Topics in Statistics
Data Analysis
Select one of the following:		12
6.555[J]	Biomedical Signal and Image Processing
6.869	Advances in Computer Vision
9.073[J]	Statistics for Neuroscience Research
9.272[J]	Topics in Neural Signal Processing
18.367	Waves and Imaging
IDS.131[J]	Statistics, Computation and Applications
Total Units		24

1	Students may petition to use IDS.160 to fulfill the Computation and Statistics requirement, if not elected as part of the Common Core.

Mechanical Engineering

Computation and Statistics
2.168	Learning Machines	12
or 6.860[J]	Statistical Learning Theory and Applications
Data Analysis
2.122	Stochastic Systems	12
or 2.29	Numerical Fluid Mechanics
Total Units		24

Political Science

Computation and Statistics
Select one of the following:		12
6.867	Machine Learning
9.520[J]	Statistical Learning Theory and Applications
14.381	Applied Econometrics
Data Analysis
Select one of the following:		12
17.802	Quantitative Research Methods II: Causal Inference
17.804	Quantitative Research Methods III: Generalized Linear Models and Extensions
17.806	Quantitative Research Methods IV: Advanced Topics
Total Units		24

Social and Engineering Systems

Computation and Statistics
Select one of the following:		12
6.434[J]	Statistics for Engineers and Scientists
6.438	Algorithms for Inference
6.867	Machine Learning
9.520[J]	Statistical Learning Theory and Applications
14.381	Applied Econometrics
14.382	Econometrics
15.077[J]	Statistical Machine Learning and Data Science
17.802	Quantitative Research Methods II: Causal Inference
17.804	Quantitative Research Methods III: Generalized Linear Models and Extensions
17.806	Quantitative Research Methods IV: Advanced Topics
Data Analysis
Select one of the following:		12-15
6.555[J]	Biomedical Signal and Image Processing
6.869	Advances in Computer Vision
9.073[J]	Statistics for Neuroscience Research
9.272[J]	Topics in Neural Signal Processing
14.386 & 14.192	New Econometric Methods and Advanced Research and Communication
14.387 & 14.192	Applied Econometrics and Advanced Research and Communication
18.367	Waves and Imaging
IDS.131[J]	Statistics, Computation and Applications
Total Units		24-27