2009-2011 - Benedict College

MATHEMATICS AND COMPUTER SCIENCE DEPARTMENT 237
samples and sampling distributions, sampling and nonsampling errors; estimation, determination of
the sample size, use of statistical software packages; hypothesis testing, relationship between hypothesis
testing and confidence interval estimation; hypothesis concerning the population variance and
standard deviation; hypothesis testing two populations; analysis of variance, simple regression and
correlation, multiple correlation and regression; nonparametric statistics; statistical decision making.
Prerequisite: Math 236.
Math 436 Applied Probability
credit 3 hrs.
This course is designed as an intermediate course in applied probability for students in mathematics,
computer science, physics -engineering, management, and biological and physical science. It is also
recommended for students in Teaching of Mathematics. The course covers basic probability; discrete
random variables; joint distributions and independent random variables; expected values; covariance
and correlation; special discrete random variables; (binomial, geometric, negative binomial, hypergeometric),
multinomial, and Poisson, moments and moment generating functions; Markov Chains;
Markov property, simple queuing systems, steady-state probabilities, continuous random variables,
probability density functions; joint probability distributions; special continuous random variables; (exponential,
normal, gamma, and Weibull); and counting and queuing processes, (Bernoulli, Poisson).
Prerequisite: Math 144, Math 230 and CSc 135 or CSc 136.
Math 437 Mathematical Analysis I
credit 3 hrs.
Techniques of proof, sets, functions, structure of real numbers, the completeness axiom, density of
rational numbers in real numbers, epsilon-delta argument, sequences to include convergence, limit
theorems, monotone sequences and subsequences, continuity of functions, continuity and sequences,
differentiation to include definitions and Mean Value Theorem. Prerequisite: Math 144.
Math 438 Mathematical Analysis II
credit 3 hrs.
Course covers sequences (revisited), Bolzano-Weierstrass Theorems, Cauchy sequences, limits at
infinity; continuity of functions to be revisited including limits of functions, uniform continuity, and discontinuities,
integrals and its properties, the Fundamental Theorem of Calculus, convergence and
divergence of infinite series, absolute and conditional convergence, sequences and series of functions,
power series. Prerequisite: Math 437.
MC 431 Numerical Analysis I
credit 3 hrs.
Course covers interpolation; approximations; numerical differentiation and integration. Prerequisites:
Math 136, Math 144 and CSc 138.
MC 432 Numerical Analysis II
credit 3 hrs.
Course covers numerical techniques in linear algebra. Numerical solution of transcendental equations,
systems of linear equations, Milne's method, Runge-Kutta method, modeling of continuous discrete
systems, approximation to computer based functions, and Pade's approximation. Prerequisite: Math
431.