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 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.

Foundation (select one)

2.087 Engineering Mathematics: Linear Algebra and ODEs
6.0001 Introduction to Computer Science Programming in Python and 6.0002 Introduction to Computational Thinking
6.01 Introduction to EECS via Robotics
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.

Contact

IDSS Academic Office
email
phone: 617-324-4934
E17-462B

Accessibility

Academics