Quantitative Methods

Students with strong quantitative backgrounds have positioned themselves at the top of the job-seeking pool. The Quantitative Methods concentration provides tools and techniques that are widely applied in a variety of fields in business such as corporate management, investment banking, consulting, information technology, finance, economics, and marketing. This concentration focuses on applied problem-solving methodologies where quantitative models are built and used to facilitate the decision-making process.

In addition, the courses in this concentration are designed to offer a fine balance between depth and breadth, relevance and rigor, critical and analytical thinking.

Sponsored by: Math and Science Division

Faculty Contact: Michelle Li (email: dli@babson.edu

Faculty contacts serve as advisers to those students who have an interest in the given concentration. You should feel free to contact these faculty with questions.

Required Courses

In addition to QTM 1000 and QTM 1010:

A) QTM 2600 Linear Algebra and Dynamical Systems

B) Choose two of the following:

  • QTM 2601 Applications of Discrete Mathematics
  • QTM 2622 Sports Application of Mathematics​
  • QTM 3620 Optimization Methods and Applications (Previously titled: Operations Research) 
  • QTM 3674 Cryptology and Coding Theory
  • QTM 3675 Probability for Risk Management

C) Choose one of the following:

  • QTM 2623 Programming with R for Business Analytics
  • QTM 3605 Quantitative Analysis of Structural Injustice
  • QTM 3610 Applied Multivariate Statistics
  • QTM 3615 Time Series Analysis and Forecasting
  • QTM 3625 Financial Simulation
  • QTM 3635 Quantitative Methods for Machine Learning

QTM 2000 is not a requirement nor is it an elective counting towards this concentration.

*If approved by the division chairperson, one of these courses could be replaced by a QTM selected topics or independent study research project.

Courses Suggested But Not Required
  • MIS 3640 Problem Solving and Software Design
  • ENGR 1510 Introductory Programming (F.W. Olin College of Engineering) ​​​