Go to Main Content

Ramapo College Information System

 

HELP | EXIT

Detailed Course Information

 

Fall 2021
May 18,2022
Transparent Image
Information Select the desired Level or Schedule Type to find available classes for the course.

MATH 390 - ADVANCED TOPICS
The descriptions and topics of this course vary from semester-to-semester, as well as from instructor-to-instructor. Prerequisite: varies with the topic offered. MATH 390 GRAPH THEORY. This course will provide a friendly introduction to graph theory. The primary focus of this class is to highlight the importance of graph theory in modern mathematics. Topics that underscore its utility include the basic properties of graphs, invariants of graphs, common families of graphs, adjacency matrix of a graph and its properties, colorings, connectivity, trees, forests and spanning trees. MATH 390 LINEAR OPTIMIZATION. Linear Optimization is concerned with methods to allocate limited resources in an optimal way. Linear constraints are imposed on variables representing those resources. Among the variable values satisfying the restrictions, those that maximize or minimize a linear function of the unknowns are looked for. The Simplex Method, an algorithm to solve linear programs will be discussed. Several applications of interest for mathematics or computer science students will be presented: production processes, allocation of personnel and other scheduling problems, transportation problems, diet problems, among others. MATH 390 MATHEMATICAL MODELING. This course is designed to introduce students to fundamental concepts and methods of mathematical modeling. We will study many model types, and learn techniques to construct and analyze appropriate models for a variety of applications. We will additionally build students' understanding of the general model-building process and develop a strong foundation with which students can confidently tackle real-world, open-ended problems. Topics may include discrete and continuous dynamical systems, proportionality and geometric similarity models, fitting models to data, simulations, probabilistic modeling, decision theory, or network science. PARTIAL DIFFERENTIAL EQUATIONS: This is an introduction to partial differential equations that will cover first-order equations, linear second-order equations, separation of variables, solutions by series expansions, and boundary value problems. There will be some emphasis on equations related to physics, such as the heat equation and wave equation.
0.000 TO 4.000 Credit hours
0.000 TO 4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Hybrid, Lecture, Online Course

Mathematics Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Undergraduate

Prerequisites:
FOR MATH 390

General Requirements:
Course or Test: MATH 237
Minimum Grade of D
May not be taken concurrently.  )
or
Course or Test: MATH 205
Minimum Grade of D
May not be taken concurrently. )


Return to Previous New Search
Transparent Image
Skip to top of page
Release: 8.7.2.4