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.

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

  • 6.100A (6.0001) Introduction to Computer Science Programming in Python and 6.100B(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
  • 18.061  Linear Algebra and Optimization

Statistics 1 (select one)

  • 1.010 Introduction to Probability and Statistics in Engineering
  • 6.3700 (6.041) Introduction to Probability
  • 9.07 Statistics for Brain and Cognitive Science
  • 14.30 Introduction to Statistical Methods in Economics
  • 15.069 Applied Probability and Statistics
  • 16.09  Statistics and Probability
  • 18.600 Probability and Random Variables

Statistics 2 (select one)

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

Computation & Data Analysis (select two)

  • 1.00 Engineering Computation and Data Science
  • 2.086 Numerical Computation for Mechanical Engineers
  • 6.3800 (6.008) Introduction to Inference
  • 6.3900 (6.036) Introduction to Machine Learning
  • 6.8711 (6.802[J]) Foundations of Computational and Systems Biology
  • 6.8301 (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(Prerequisites: (6.100B, (18.03, 18.06, or 18.C06), and (6.3700, 6.3800, 14.30, 16.09, or 18.05))


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:

6.7830 (6.435), 6.7700 (6.436[J]), 6.7800 (6.437), 6.7810 (6.438), 6.7900 (6.867),
6.8300 (6.869), 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

How to Apply

To apply for the Minor in Statistics and Data Science, please fill out the minor application form.  After submitting the form, you will be paired with a minor advisor (minor advisors cannot be from your home department).  Course substitution requests may cause a delay in the process.


IDSS Academic Office
phone: 617-324-4934

MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307