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INTERDISCIPLINARY PROGRAM

Mathematics – Decision Science

The mathematics-decision science major is concerned with using mathematics to make appropriate decisions when confronted with complex problems. It can deal with optimizing the design or operation of systems involving machinery, materials, money and even people.

This interdisciplinary program uses courses from the Falls School of Business to enhance the Mathematics major without requiring a double major. The result is a program more focused than a traditional Mathematics major, yet still versatile for a broad range of career paths.

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Program

This program is interdisciplinary.

This major is taught by our talented faculty across campus, including professors from the Falls School of Business and the Department of Mathematics.

This major can be completed in a 3-year or 4-year track to graduation.

Classes

What courses will I take?

Among the classes in the 53-hour major are:

  • differential equations
  • linear algebra
  • marketing research
  • numerical analysis
  • principles of management
  • problem seminar
  • supply chain management

View the courses required for the Mathematics – Decision Science Major.

 

Mathematics Student Research

The Anderson University Department of Mathematics offers a unique, hands-on research experience.   Undergraduate students work alongside faculty to conduct original research in mathematics.  This exciting research into new mathematics is presented in a variety of venues.  These have included poster sessions and invited talks at other universities.  Opportunities such as these advance our knowledge about God’s creation and develop skills that are essential for students furthering their studies at the graduate level.

Here are samples of the projects that are currently underway:

Adventures in the Quantum Polynomial Ring:  Linear Algebra Computations in C Abstract:

  • The p-polynomials appear as the elements of transition matrices used to convert a special class of bases to the standard basis within the quantum polynomial ring. We examined computational methods for generating p-polynomials. An algorithm for finding a p-polynomial has been known; however, the implementation of this algorithm was not sufficiently fast. Through algorithmic analysis, a change in the implementation language, and the adoption of matrix-based algorithms, significant improvements in speed were realized. Optimization of this process has led to a speedup of over 140,000 times.
  • Linear Algebra Computations in C Research Project [PDF]

Adventures in the Quantum Polynomial Ring: Patterns in the p-Polynomials Abstract:

  • The p-polynomials appear as the elements of transition matrices used to convert a special class of bases to the standard basis within the quantum polynomial ring. The purpose of this study is to analyze these polynomials for patterns and eventually catalog these newly generated p-polynomials for future analysis. The initial strategy for finding these patterns will take advantage of generalized rules from the modified R-polynomials and Kazhdan-Lusztig polynomials. Additional strategies arise by observing new patterns from the list of computer-generated polynomials. We also examine a special class of p-polynomials that are generated by the longest word in the symmetric group and describe patterns in the coefficients of these polynomials.
  • Patterns in the p-Polynomials [PDF]

On the Creation of Rank Two Centrosymmetric Matrices

  • For any square matrix B, we can create a centrosymmetric matrix A = B+JBJ where J is the skew identity matrix. If the matrix B is created as the outer product of two vectors v and h, the resulting centrosymmetric matrix has a maximal rank of 2. However, not all such rank two matrices can be written in this form. In this work, we fully examine when a 3 x 3 centrosymmetric matrix can be created from two vectors and generalize our results to larger matrices.
  • Creation of Rank Two Centrosymmetric Matrices [PDF]

If you have difficulty accessing the information in the above PDF files, please contact us.

 

Mathematics Facilities

Located on the third floor of Decker Hall, the AU Department of Mathematics is an open and inviting space.  Four faculty offices open into a common area with whiteboard walls. All who pass through can see mathematics being done.

Decker 338 is a classroom that has been specially designed for mathematics courses. Distinctive features include floor to ceiling whiteboard walls and easily movable furniture. Tables in the room provide ample space for notebooks, textbooks, and a laptop. The versatile nature of the furniture allows the room to be transformed to accommodate lectures with 35 students, students working in groups, and smaller seminar based courses.

Decker 330 serves as the department's mathematics lab. This room is used for tutoring, seminar space, and a place where students can work on projects together.

Our Faculty & Staff

Bruce

Dr. Michael L. Bruce

Collette

Dr. Michael E. Collette

Amanda Drayer

Amanda Drayer

Dulaney

Dr. Emmett Dulaney

Earl

Toni Earl

Fox

Dr. Jerrald M. Fox

Haskett

Dr. Rebecca A. Haskett

Hochstetler

Dr. Jay J. Hochstetler

Photo of Justin Lambright

Dr. Justin Lambright

Lucas

Dr. Doyle J. Lucas

Peddicord

Dr. Melanie Peddicord

Pianki

Dr. Francis O. Pianki

Photo of Paul Saltzmann

Paul Saltzmann

Shin

Dr. Hyeon Joon Shin

Stumpf

Prof. Anna Stumpf

Ray Sylvester

Dr. Ray Sylvester

Photo of Courtney Taylor

Dr. Courtney Taylor

Fsblist Tijerina

Prof. Vanessa Tijerina

Truitt

Dr. Terry Truitt

Photo of Gerard Lee Van Groningen

Dr. Gerard Lee Van Groningen

Vaughters

Dr. Brock Vaughters