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 Probability12
or 18.175 Theory of Probability
18.655Mathematical Statistics12
IDS.190Doctoral Seminar in Statistics and Data Science3
Total Units27

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
Algorithms for Inference
Machine Learning
Statistical Learning Theory and Applications
Statistics for Engineers and Scientists
Numerical Methods for Stochastic Modeling and Inference
Data Analysis
Select one of the following:12
Statistical Communication and Localization Theory
Statistical Methods in Experimental Design
Statistics, Computation and Applications
Total Units24

Economics

Computation and Statistics
Select one of the following: 112
Statistical Learning Theory and Applications
Machine Learning
Data Analysis
14.386New Econometric Methods12
or 14.387 Applied Econometrics
14.389Econometrics Paper3
Total Units27
1

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

Mathematics

Computation and Statistics
Select one of the following:12
Nonlinear Optimization
Algebraic Techniques and Semidefinite Optimization
Algorithms for Inference
Machine Learning
Statistical Learning Theory and Applications
Numerical Computing and Interactive Software
Eigenvalues of Random Matrices
Advanced Algorithms
Randomized Algorithms
Topics in Statistics
Data Analysis
Select one of the following:12
Biomedical Signal and Image Processing
Advances in Computer Vision
Statistics for Neuroscience Research
Topics in Neural Signal Processing
Waves and Imaging
Statistics, Computation and Applications
Total Units24

Political Science

Computation and Statistics
Select one of the following:12
Machine Learning
Statistical Learning Theory and Applications
Statistical Method in Economics
Data Analysis
Select one of the following:12
Quantitative Research Methods II: Causal Inference
Quantitative Research Methods III: Generalized Linear Models and Extensions
Quantitative Research Methods IV: Advanced Topics
Total Units24

Social and Engineering Systems

Computation and Statistics
Select one of the following:12
Statistics for Engineers and Scientists
Algorithms for Inference
Machine Learning
Statistical Learning Theory and Applications
Statistical Method in Economics
Econometrics
Statistical Learning and Data Mining
Quantitative Research Methods II: Causal Inference
Quantitative Research Methods III: Generalized Linear Models and Extensions
Quantitative Research Methods IV: Advanced Topics
Data Analysis
Select one of the following:12-15
Biomedical Signal and Image Processing
Advances in Computer Vision
Statistics for Neuroscience Research
Topics in Neural Signal Processing
New Econometric Methods
and Econometrics Paper
Applied Econometrics
and Econometrics Paper
Waves and Imaging
Statistics, Computation and Applications
Total Units24-27