Quantitative Methods
Math-minded students thrive in the quantitative methods concentration, which provides quantitative business methods and analysis tools that can be widely applied in a variety of fields.
This concentration focuses on applied problem-solving methodologies where quantitative models are built and used for quantitative decision making. In addition, quantitative analysis courses in this concentration are designed to offer a fine balance between depth and breadth, relevance and rigor, and critical and analytical thinking.
Where the Quantitative Methods Concentration Will Take You
Understanding statistical forecasting and quantitative business analysis, including how to decipher and use data strategically, is a skill entrepreneurial leaders use to turn problems into opportunities. Being able to predict outcomes using time series forecasting mehtods, and other strategies means taking risks doesn’t scare you and you can pivot when challenges arise.
The quantitative methods for business concentration provides tools and techniques such as corporate management, investment banking, consulting, information technology, finance, economics, ecommerce, and marketing.
Babson students who take quantitative analyst courses have gone on to work as consultants in sports and entertainment, cyber security experts and analysts, and leaders in the operation divisions of companies, including their own.
What You Will Study in Your Quantitative Methods Courses
To complete this concentration, you will need to complete four advanced quantitative business methods courses. Your options include:
A Babson course always finds practical applications for the theoretical. This time-series-forecasting methods course is no different, as you analyze time series data in the context of various real-life forecasting situations such as banking, healthcare, sports, and global warming. You gain practical experience with time series data and get comfortable predicting future outcomes, comparing alternative models, and communicating your results and suggestions clearly.
The ease of data collection coupled with plummeting data storage costs over the last decades have resulted in massive amounts of data that many business organizations have at their fingertips. Effective analysis of those data followed by sound decision-making is what makes a company an analytical competitor. In this quantitative analyst course, you will learn how to apply advanced quantitative tools for solving complex machine learning problems.
Mathematicians and statisticians are playing an increasing role in shaping how athletic contests are played and how they are judged. This course examines some of the underlying quantitative principles that are routinely used. You will apply some statistical techniques (expectations, probability and risk/reward judgments) and some that are deterministic (optimization, ranking and validation.) A variety of software packages will be used to demonstrate the many ways that a mathematical point of view can inform athletes, trainers, administrators, and fans.
- Applications of Discrete Mathematics
- Applied Multivariate Statistics
- Cryptology and Coding Theory
- Financial Simulation
- Linear Algebra
- Optimization Methods and Applications
- Probability for Risk Management
- Programming with R for Business Analytics
- Quantitative Analysis of Structural Injustice
- Quantitative Methods for Machine Learning
Explore the entire list of undergraduate courses
You Will Learn From the Best
At Babson, our faculty are experts, innovators, and forward thinkers in their chosen fields. Here are just some professors sharing their expertise and support with our students in the quantitative methods program.
Richard Cleary
Rick Cleary is a statistician and mathematician with research and consulting interests in a variety of fields including sports and education. Prior to coming to Babson College in 2013, he taught at St. Michael’s College in Vermont, Cornell University, Bentley University, and Harvard University. He has held leadership positions in the Mathematical Association of America, including six years on the Executive Committee as Associate Treasurer. He currently co-chairs the Upper Division Pathways initiative for TPSE Math.
Michelle Li
Michelle Li’s research and teaching interests lie in the domains of operations research, game theory, business analytics, supply chain network management, humanitarian logistics, and sustainable systems. She studies the economics, equilibrium, and dynamics of game theoretic supply chain networks, with applications to sustainability, corporate social responsibility, outsourcing, information asymmetry, and humanitarian blood banking.
Have Questions?
Faculty Contact: Michelle Li
Sponsoring Division: Mathematics, Analytics, Science, and Technology
