The bachelor of sciences degree program in mathematics at WVU Tech offers rigorous training in four major branches of mathematics; analysis, algebra, topology and geometry, and applied mathematics. Students also obtain solid knowledge in computer science, physics, and other sciences/engineering.
Through a well-constructed curriculum, our graduates will be critical thinkers and problem solvers, will be able to understand concepts, solve problems, and prove theorems in at least three of the four major areas of mathematics; will be able to develop computer programs to implement computational algorithms; and will be able to communicate effectively.
Because WVU Tech is a STEM institution, students are encouraged to supplement their studies in mathematics with courses from engineering and science. We offer small classes and excellent advising by our dedicated, well-educated faculty. Students also have an opportunity to double-major in mathematics and engineering at WVU Tech.
Students who are interested in mathematics, perform well in high school math classes and have high math scores on ACT/SAT exams tend to do well in the math program.
Casey Orndorff completed his master’s degree in mathematics and a Ph.D. in computational analysis and modeling in Louisiana, where he spent his time researching the effects of treatments for cancer patients. Now he shares his passion for the field with his own students as a mathematics professor.
“In a way, you can compare curing cancer to an open-ended math problem —where the solution could save countless lives.”
Our graduates have been employed in state government, financial groups and insurance companies.
We also provide our graduates with the foundation for graduate education in mathematics or related fields. Many of our graduates have continued their graduate studies in universities throughout the nation.
Graduates with a four-year degree in mathematics often find work in positions such as:
Learn about permutations, combinations, binominal theorem, inclusion-exclusion formula, recurrence relations, generating functions, elementary graph theory (connectivity, paths, circuits, trees, vertex and edge coloring, graph algorithms) matching theory and discrete optimization.
Explore samples spaces; probability, definition and elementary properties; random variables, expectation; special distributions; estimation; hypothesis testing; and linear regression.
This course is an introduction to metric and topological spaces. Topics include: continuity, convergence, separation, compactness and connectedness.