COMP 172 Discrete Structures for Computer Science

An introduction to and survey of the mathematics used in computer science including functions, relations, sets, counting, logic, Boolean
algebra, proof techniques, induction, recursion, computational complexity, and computability. Other topics may be included as time
permits.

MATH 201 Transition to Advanced Mathematics

A thorough introduction to the reading, writing, presenting and creating of mathematical proofs. Students will learn and practice in a
careful and deliberate way the techniques used to prove mathematical theorems. Proofs studied will be chosen from a variety of fields
such as set theory, number theory, analysis, algebra, and graph theory. Topics also include elements of the history and philosophy of
mathematics and an introduction to the mathematical community.

PHIL 206 Logic

An examination of argumentation, with emphasis on identifying, analyzing, and evaluating arguments. Issues to be considered include categorical, propositional, and predicate logic.

MATH 211 Applied Statistics for the Formal & Natural Sciences

This course is modern introduction to statistical inference. Topics of the course relate to inferential techniques for one, two, and multiple samples. Both classical and resampling methods will be used. The course will also include the basic concepts of experimental design. A professional statistical software package will be used. Students may not earn credit for both Math 111 and Math 211.

 

PSYC 211 Statistical Methods

Statistical methods are an integral part of social sciences, particularly psychology, as they provide the tools that are needed to reveal patterns in complex behavior. Students will develop an appreciation of the role of statistics and knowledge of the major tests that demonstrate differences and relationships. Math 111 cannot be substituted for this course.

MATH 214 Discrete Mathematical Modeling with Biological Applications

This course provides an introduction to a variety of mathematical topics used in analyzing problems arising in the biological sciences, without using calculus.  The mathematics covered in this course all revolve around modeling dynamic biological phenomenon using discrete time steps. Specifically, we will construct and analyze discrete difference equation models, matrix models, and Boolean models.

MATH 223 Multivariable Calculus

A continuation of Math 122 covering sequences, series, and the calculus of multivariable functions.  Topics include power series, Taylor series, functions of several variables, partial derivatives, and multivariable integration.

INTD 225 Geographic Information Systems (GIS)

This course introduces students to Geographic Information Systems (GIS) through the analysis of spatial data. Students use deductive
reasoning and logic to interpret data, draw conclusions based on numerical and spatial data, learn spatial statistics, and examine the
different ways to represent data. Students also learn to construct, run and apply spatial models. An emphasis is made on the application
of GIS to real-world situations.

MATH 251 Differential Equations

The theory, methods, and applications of ordinary differential equations. Topics include existence, uniqueness and other properties of
solutions, linear equations, power series and Laplace transform methods, systems of linear equations, and qualitative analysis.

MATH 261 Linear Algebra

Topics include systems of linear equations, matrix algebra, determinants, real and complex vector spaces, linear transformations,
eigenvalues and eigenvectors, and diagonalization. Attention is given to proofs.