Dana Fine, PhD

An intensive study of advanced algebra and trigonometry. Topics include: linear, quadratic, polynomial, rational, exponential, logarithmic and trigonometric functions, modeling and graphing these functions, and the effects of affine transformations on the graphs of functions. This course prepares students for the study of Calculus I (MTH 151 or MTH 153), which is required for majors in Mathematics, Physics, Chemistry, Engineering and Mathematical/Computational Biology. This course fulfills the general Calculus I prerequisites for Mathematics, Physics, Chemistry, Engineering and Mathematical/Computational Biology majors who matriculated prior to Fall 2012 and has been approved by University Studies Curriculum for students matriculating in Fall 2012 or later.

An introduction to mathematical reasoning, mathematical logic, and methods of proof. Topics include: properties of numbers, elementary counting methods, discrete structures, Boolean algebra, introduction to directed and undirected graphs, methods of proof, and applications in mathematics and computer science. This is the first semester of a discrete mathematics sequence designed for Mathematics, Computer and Information Sciences majors. This course fulfills the general education core requirements for Mathematics, Computer and Information Sciences majors who matriculated prior to Fall 2012 and has been approved by University Studies Curriculum for students matriculating in Fall 2012 or later.

A study of mathematical foundations for advanced mathematics and theoretical computer science. Topics include: mathematical reasoning including mathematical induction, combinatorial analysis including simple probability, discrete structures (such as sets, recursions, relations, and trees), algorithmic thinking, applications, and modeling (such as combinatorial circuits). This is the second semester of a discrete mathematics sequence designed for Mathematics and Computer Information Sciences majors. This course fulfills the general education core requirements for Mathematics, Computer and Information Sciences majors who matriculated prior to Fall 2012 and has been approved by University Studies Curriculum for students matriculating in Fall 2012 or later.

Modeling small-world networks. This experiential-learning course focuses on the simulation and analysis of small ­world networks, including social networks, food chains and the world-wide web. Models will include regular lattices, random graphs, Strogatz-Watts networks, an random accretion models of Barabasi and Albert and of Aeillo, Chung and Lu.

Modeling small-world networks. This experiential-learning course focuses on the simulation and analysis of small ­world networks, including social networks, food chains and the world-wide web. Models will include regular lattices, random graphs, Strogatz-Watts networks, an random accretion models of Barabasi and Albert and of Aeillo, Chung and Lu.

Modeling small-world networks. This experiential-learning course focuses on the simulation and analysis of small ­world networks, including social networks, food chains and the world-wide web. Models will include regular lattices, random graphs, Strogatz-Watts networks, an random accretion models of Barabasi and Albert and of Aeillo, Chung and Lu.

Modeling small-world networks. This experiential-learning course focuses on the simulation and analysis of small ­world networks, including social networks, food chains and the world-wide web. Models will include regular lattices, random graphs, Strogatz-Watts networks, an random accretion models of Barabasi and Albert and of Aeillo, Chung and Lu.