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 becoming 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. This aspect of managing and processing data is popularly referred to as  “data science.”

Through six 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.

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.

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Foundation (select one)

  • 2.087 Engineering Mathematics: Linear Algebra and ODEs
  • 6.01 Introduction to EECS I
  • 6.0001 Introduction to Computer Science Programming in Python, and 6.0002 Introduction to Computational Thinking and Data Science
  • 18.03 Differential Equations
  • 18.06 Linear Algebra

Statistics 1 (select one)

  • 1.010 Uncertainty in Engineering
  • 6.041A Introduction to Probability I and 6.041B Introduction to Probability II
  • 14.30 Introduction to Statistical Methods in Economics
  • 18.600 Probability and Random Variables

Statistics 2 (select one)

  • 14.32 Econometrics
  • 15.075[J] Statistical Thinking and Data Analysis
  • 18.650 Statistics for Applications

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
  • 9.07 Statistics for Brain and Cognitive Science
  • 14.31 Data Analysis for Social Scientists
  • 14.36 Advanced Econometrics
  • 15.053 Optimization Methods in Business Analytics
  • 15.0791 Introduction to Applied Probability
  • 16.09 Statistics and Probability
  • 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 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:

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.

  • Victor Chernozhukov                                    Economics
  • David Gamarnik                                            Management
  • Youssef Marzouk                                           Aero & Astro
  • Anna Mikusheva                                            Economics
  • Philippe Rigollet                                            Math
  • Devavrat Shah                                                EECS

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, bring a minor application to the IDSS offices (E17-462A), along with an unofficial copy of your transcript (available from the Student Services Center, 11-120).


IDSS Academic Office
phone: 617-324-4934