Applied Mathematics Program at Fredonia
The Bachelor of Science in Applied Mathematics is a degree program that prepares you to use the tools and concepts of mathematics and statistics to solve problems in the real world, whether in STEM, business, industry, or the public sector. Graduates with strong quantitative and data skills are in high demand across all economic sectors.
The Fredonia Difference
Within the Applied Math major, students choose to focus on finance and economics, statistics and data, or science. If you couple the major with a second major or minor in an area of application, you can customize your preparation for a wide variety of careers. Fredonia also offers advisement and coursework for Actuarial Science, a high-demand career that involves applying the tools of statistics and finance to problems in the insurance sector.
Career Opportunities for Applied Mathematics
- Industrial engineer
- Data scientist
- Financial planner
- Software engineer
- Systems analyst
- Financial analyst
It's Different Here
All tenured faculty in the Department of Mathematical Sciences hold a Ph.D. degree.
Compete and succeed
Fredonia students regularly compete in national applied math and modeling competitions.
Students in upper-level classes
Class sizes are not large, around 20 students at the junior-senior level.
Why Applied Mathematics at Fredonia?
Our study room for students is a legendary space on campus. This large, comfortable room is located in the heart of the department, with faculty offices just steps away on all sides.
We help students select programs, coursework, and professional experiences to prepare them for their post-graduate goals.
One of the top-ranked careers in terms of work environment, job security, and salary. Actuaries apply tools from statistics and finance to solve problems in the insurance industry.
MATH 329 Mathematical Modeling
An introduction to the development of mathematical models to solve various applied and industrial problems. Topics will include optimization, Lagrange multipliers, sensitivity analysis in optimization models, analysis and simulation of discrete and continuous dynamic models.
STAT 350 Probability and Statistics
Basics of probability; descriptive statistics; discrete and continuous distributions; confidence intervals and tests of hypotheses concerning means and proportions; simple linear regression; statistical software.
MATH 406 Applied Math Senior Seminar
Students are partitioned into small groups and given problems from the Mathematical Contest in Modeling, or similar material, to work on together. Written reports and formal presentations will be required.