Minor in Statistics and Data Science

MIT’s Minor in Statistics and Data Science is available to MIT undergraduates from any major.

Statistics is the science of making inferences and decisions under uncertainty.  It is increasingly relevant in the modern world due to the widespread availability of and access to unprecedented amounts of data and computational resources. Unlike classical statistics, the need to process and manage massive amounts of data has become a key feature of modern statistics, and is commonly referred to as data science.

Through seven required subjects, the Minor in Statistics and Data Science focuses on providing students with a working knowledge base in statistics, probability, and computation, along with an ability to perform data analysis.

*Please Note:  Changes in the prerequisites for the capstone (IDS.012) have split the former Foundation course into two requirements (Foundation One and Two) to assure all students in the minor will have completed the expected prerequisites.  The change to the capstone requirements will not be official until 2022, but we highly recommend all Stats minors complete the Foundation One requirement to be properly prepared for IDS.012.

A minimum of four subjects taken for the statistics and data science minor cannot also count toward a major or another minor.  Please contact us with further questions.

Foundation One (select one)

  • 6.01 Introduction to EECS via Robotics
  • 6.0001 Introduction to Computer Science Programming in Python and 6.0002 Introduction to Computational Thinking

Foundation Two (select one)

  • 2.087 Engineering Mathematics: Linear Algebra and ODEs
  • 18.03 Differential Equations
  • 18.06 Linear Algebra

Statistics 1 (select one)

  • 1.010 Introduction to Probability and Statistics in Engineering
  • 6.041A Introduction to Probability I and 6.041B Introduction to Probability II
  • 9.07 Statistics for Brain and Cognitive Science
  • 14.30 Introduction to Statistical Methods in Economics
  • 15.0791  Introduction to Applied Probability
  • 16.09  Statistics and Probability
  • 18.600 Probability and Random Variables

Statistics 2 (select one)

  • 14.32 Econometric Data Science
  • 15.075[J] Statistical Thinking and Data Analysis
  • 18.650[J]  Fundamentals of Statistics

Computation & Data Analysis (select two)

  • 1.00 Engineering Computation and Data Science
  • 2.086 Numerical Computation for Mechanical Engineers
  • 6.008 Introduction to Inference
  • 6.036 Introduction to Machine Learning
  • 6.802[J] Foundations of Computational and Systems Biology
  • 6.819 Advances in Computer Vision
  • 14.36 Advanced Econometrics
  • 15.053 Optimization Methods in Business Analytics
  • 16.90 Computational Modeling and Data Analysis in Aerospace Engineering
  • 18.065  Matrix Methods in Data Analysis, Signal Processing and Machine Learning
  • 18.642 Topics in Mathematics with Applications in Finance

Capstone Subject (required)

  • IDS.012[J] Statistics, Computation and Applications


Graduate Subjects

The graduate subjects listed below have been preapproved by the Statistics Curriculum Committee (D. Shah & D. Gamarnik, co-chairs) as suitable statistics coursework for advanced undergraduates. After receiving approval from your minor advisor, students may petition to take one of these subjects in lieu of one of the undergraduate subjects listed above.  Note, IDS.012 can only be switched with the graduate-level version of the same class, IDS.131:

6.435, 6.436[J], 6.437, 6.438, 6.867, 9.073, 9.272[J], 11.220, 14.387, 15.034, 15.062[J], 15.068, 15.071, 16.391[J], 16.470[J], 16.940, 17.800, 18.655


Minor Advisors

Minor advisors must be from outside the student’s major field of study.

  • Emery Brown                                                Brain and Cog. Science
  • Victor Chernozhukov                                    Economics
  • Daniel Frey                                                    Mechanical Engineering
  • David Gamarnik                                            Management
  • Youssef Marzouk                                           Aero/Astro
  • Anna Mikusheva                                            Economics
  • Ankur Moitra                                                 Math
  • Philippe Rigollet                                            Math
  • Devavrat Shah                                                EECS (unavailable for 2021)
  • Roy Welsch                                                    MIT Sloan
  • Teppei Yamamoto                                          Political Science

You are welcome to discuss your interest in the minor with any of the faculty members listed above. With your application, please list your top three choices for a minor advisor.

How to Apply

To apply for the Minor in Statistics and Data Science, please fill out the minor application form.


IDSS Academic Office
phone: 617-324-4934

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