Also offered through the Division of Continuing Studies.

Antiderivatives and indefinite integration. Rules of integration (substitution and integration by parts). Riemann sums, definite integrals and the Fundamental Theorem of Calculus. Numerical techniques for approximating definite integrals. Applications of definite integrals to problems in business and economics, and to the evaluation of probabilities and expected values. Improper integrals and their evaluation. Linear systems of equations and their solutions. Matrices and matrix operations. Matrix representation of linear systems and Gaussian elimination.

Note : Distance Learning computer system requirements

Foundations of Probability and Statistics. Brief review of set operations. Definitions and examples of sample space and probability space. Random variables, various discrete and continuous distributions. Mean, variance and general expectations. Sampling, tests of hypothesis for mean and variance, power of tests.

Vector-valued functions; curves. Functions of several variables; partial derivatives, Taylor's formula, extreme value problems. Vector fields, gradient, divergence, curl. Multiple integrals. Line and surface integrals. Green's, divergence and Stokes' theorems.

Ordinary differential equations: theory, methods of solution and applications of first order and higher order linear. Limit of sequences. Infinite series: definition of convergence, tests. Series of functions: uniform convergence, power series, Taylor polynomials and remainder, Taylor series and applications.

Vector-valued functions, curves. Functions of serveral variables. Partial derivatives. Extreme values. Scalar and vector fields. Gradient, divergence, curl. Line and surface integrals. Green's, divergence and Stokes' theorems.

Ordinary differential equations: theory, methods of solution and applications of first order and higher order linear. Limit of sequences. Infinite series: definition of convergence, tests, power series, Taylor polynomials and remainder, Taylor series and applications.

Introduction to vector spaces. Subspaces, bases and dimension. Linear transformations and matrix representations. Eigenvalues, eigenvectors and diagonalization of matrices.  Inner products; Gram-Schmidt process. An introduction to mathematical proofs and propositional logic is given throughout the course.

This course will be an introduction to cryptography including its military, political and mathematical aspects.The course will survey both historical cryptography (antiquity to 1967) and modern (post 1967) cryptography. Students succeeding in this course will understand the workings of important modern techniques including public key cryptography, key exchange protocols and elliptic curve cryptography; both modern encryption and cryptoanalysis will be covered.. More specifically, the following topics will be covered: Historical techniques such as: Alphabetic Ciphers, Frequency Analysis, Vigenere Ciphers, Kaisiski's Method, One Time Pads; The mathematical basis behind modern encryption and decryption: Basic group theory and basic properties of the integers; Modern encryption techniques such as: Public Key Cryptography, RSA, Diffie-Helman Key Exchange, Rabin Encryption, El Gamal, Discrete Log, Elliptic Curves. Modern decryption techniques such as: Birthday Attacks, Quadratic Sieve, Known Plaintext attacks, Man-in-the-middle attacks.

This course is an introduction to two types of mathematical models of games: those introduced by von Neumann and Morgenstern, which have many applications in economics, and combinatorial games. Topics from classical game theory include: two-person zero-sum games, dominant and mixed strategies, solution techniques for small games, Minimax theorem; non-zero-sum games, Nash equilbium, pure and mixed strategy equilibria. Impartial combinatorial games such as take-away games and Nim are studied, along with the Sprague-Grundy theorem and some of its applications.

An elective course for students in Arts. This course is part of the core curriculum. This course gives an introduction to information technology and its applications. Topics include an overview of computer hardware and system software, algorithm design, programming in a high level language, use of spreadsheets and data base systems, computer networks and the internet, and security considerations.