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Statistics M.S. Breadth

Other graduate courses (200 or above) may be authorized by the adviser if they provide skills relevant to degree requirements or deal primarily with an application of statistics or probability and do not overlap courses in the student's program.

There is sufficient flexibility to accommodate students with interests in applications to business, computing, economics, engineering, health, operations research, and biological and social sciences.

Graduate courses crosslisted with the Statistics Department are approved as elective credit for the program, as are the following table of suggested courses.

Suggested courses: Please use the following list as a content guideline for choosing other courses of interest that are not found here.

Biology (BIO)

BIO 244 Fundamentals of Molecular Evolution
BIO 283 Theoretical Population Genetics

Biomedical Informatics (BIOMEDIN)

BIOMEDIN 214 Representations and Algorithms for Computational Molecular Biology
BIOMEDIN 233 Intermediate Biostatistics: Analysis of Discrete Data

Civil Engineering (CEE)

CEE 203 Probabilistic Models in Civil Engineering
CEE 289 Random Vibrations

Computational and Mathematical Engineering (CME)

CME 302 Numerical Linear Algebra
CME 303 Partial Differential Equations of Applied Mathematics
CME 305 Discrete Mathematics and Algorithms
CME 306 Numerical Solution of Partial Differential Equations
CME 309 Randomized Algorithms and Probabilistic Analysis
CME 321A Mathematical Methods of Imaging
CME 323 Distributed Algorithms and Optimization
CME 364A Convex Optimization I
CME 364B Convex Optimization II

Computer Science (CS)

CS 145 Introduction to Databases
CS 205A Mathematical Methods for Robotics, Vision, and Graphics
CS 221 Artificial Intelligence: Principles and Techniques
CS 228 Probabilistic Graphical Models: Principles and Techniques
CS 229 Machine Learning
CS 246 Mining Massive Data Sets
CS 261 Optimization and Algorithmic Paradigms
CS 269O

Introduction to Optimization Theory (MS&E 213)

CS 273A A Computational Tour of the Human Genome
CS 274 Representations and Algorithms for Computational Molecular Biology

Economics (ECON)

ECON 202 Microeconomics I
ECON 203 Microeconomics II
ECON 210 Macroeconomics I
ECON 271 Intermediate Econometrics II
ECON 272 Intermediate Econometrics III
ECON 273 Advanced Econometrics I
ECON 274 Advanced Econometrics II
ECON 276 Computational Econometrics
ECON 286 Game Theory and Economic Applications
ECON 288 Computational Economics

Economic Analysis & Policy (MGTECON)

MGTECON 634 Machine Learning and Causal Inference

Education (EDUC)

EDUC 351A Statistical Methods for Longitudinal Research
EDUC 353A Problems in Measurement: Item Response Theory

Electrical Engineering (EE)

EE 261 The Fourier Transform and Its Applications
EE 278 Introduction to Statistical Signal Processing
EE 364A Convex Optimization I
EE 364B Convex Optimization II
EE 368 Digital Image Processing
EE 372 Data Science for High Throughput Sequencing
EE 373A Adaptive Signal Processing
EE 387 Error Correcting Codes: Theory and Applications
EE 388

Modern Coding Theory

Energy (ENERGY)

ENERGY 240 Geostatistics
ENERGY 241 Seismic Reservoir Characterization
ENERGY 242 Topics in Advanced Geostatistics

Engineering (ENG)

ENGR 207B Linear Control Systems II
ENGR 150 Data Challenege Lab
ENGR 350 Data Impact Lab

Genetics (GENE)

GENE 211 Genomics
GENE 245 Statistical and Machine Learning Methods for Genomics

GSB: Finance (FINANCE), General & Interdisciplinary (GSBGEN)

FINANCE 620 Financial Markets I
FINANCE 621 Financial Markets II
FINANCE 622 Dynamic Asset Pricing Theory
GSBGEN 641 Advanced Empirical Methods

Health Research and Policy (HRP)

HRP 206 Meta-research: Appraising Research Findings, Bias, and Meta-analysis
HRP 226 Advanced Epidemiologic and Clinical Research Methods

Management Science & Engineering (MSE)

MS&E 207 Interactive Management Science
MS&E 211 Linear and Nonlinear Optimization
MS&E 223 Simulation
MS&E 238 Leading Trends in Information Technology
MS&E 241 Economic Analysis
MS&E 245A Investment Science
MS&E 246 Financial Risk Analytics
MS&E 250A Engineering Risk Analysis
MS&E 250B Project Course in Engineering Risk Analysis
MS&E 251 Stochastic Control
MS&E 252 Decision Analysis I: Foundations of Decision Analysis
MS&E 260 Introduction to Operations Management
MS&E 311 Optimization
MS&E 313 Almost Linear Time Graph Algorithms
MS&E 321 Stochastic Systems
MS&E 322 Stochastic Calculus and Control
MS&E 327 Topics in Causal Inference
MS&E 335 Queueing and Scheduling in Processing Networks
MS&E 347 Credit Risk: Modeling and Management
MS&E 352 Decision Analysis II: Professional Decision Analysis
MS&E 353 Decision Analysis III: Frontiers of Decision Analysis
MS&E 355 Influence Diagrams and Probabilistics Networks

Mathematics (MATH)

MATH 205A Real Analysis
MATH 220 Partial Differential Equations of Applied Mathematics
MATH 236 Introduction to Stochastic Differential Equations

Mechanical Engineering (ME)

ME 300A Linear Algebra with Application to Engineering Computations

Philosophy (PHIL)

PHIL 266 Probability: Ten Great Ideas About Chance

Political Science (POLISCI)


Political Methodology I: Regression


Political Methodology II: Causal Inference


Political Methodology III: Model-Based Inference


Psychology (PSYCH)

PSYCH 253 Statistical Theory, Models, and Methodology

Sociology (SOC)

SOC 383 Sociological Methodology III: Models for Discrete Outcomes


Courses below 200 level are not acceptable, with the following exceptions:

Students are advised to avoid redundancy in coursework.

STATS 191 Introduction to Applied Statistics
MATH 115 Functions of a Real Variable
MATH 171 Fundamental Concepts of Analysis
CS 106A Programming Methodology
CS 106B Programming Abstractions
CS 106X Programming Abstractions (Accelerated)
CS 140 Operating Systems and Systems Programming
CS 142 Web Applications
CS 143 Compilers
CS 144 Introduction to Computer Networking
CS 145 Data Management and Data Systems
CS 147 Introduction to Human-Computer Interaction Design
CS 148 Introduction to Computer Graphics and Imaging
CS 149 Parallel Computing
CS 154 Introduction to Automata and Complexity Theory
CS 155 Computer and Network Security
CS 157 Computational Logic
CS 161 Design and Analysis of Algorithms
CS 170 Stanford Laptop Orchestra: Composition, Coding, and Performance
CS 181 Computers, Ethics, and Public Policy


Of the courses below 200, At most, one of these courses may be counted as an elective. 4
MATH 104 Applied Matrix Theory
MATH 113 Linear Algebra and Matrix Theory
STATS 116 Theory of Probability 2
If and when a higher level course has been used to fulfill the degree requirements, only one of the above courses may be used as an elective.