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Course Criteria
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3.00 Credits
An introduction to probability and statistics. Discrete and continuous random variables, mean and variance, hypothesis testing and confidence limits, Bayesian inference, nonparametric methods, Student's t, contingency tables, multifactor analysis of variance, fixed effects, random effects, mixed models, multiple regression, maximum likelihood, and logistic regression. Graphing calculator with Z, t, chi-square and F distribution functions (such as the TI-83 series) required. Calculus and the SAS software package are both used in an essential way. Prerequisite: Math 233 or permission of the instructor.
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3.00 Credits
A second course in elementary statistics with applications to life sciences and medicine. Review of basic statistics using biological and medical examples. New topics include incidence and prevalence, medical diagnosis, sensitivity and specificity, Bayes' rule, decision making, maximum likelihood, logistic regression, ROC curves and survival analysis. Prerequisites: Math 3200, or a strong performance in Math 2200 and permission of the instructor.
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3.00 Credits
Polynomials, binomial expansions, factoring, rings (integers and polynomials), unique factorization, and other topics relevant to the high school curriculum. Designed for future secondary school teachers and other students looking for a course in algebra at a less abstract level than Math 430. Prerequisite: Math 310 or permission of instructor.
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3.00 Credits
Divisibility properties of integers, congruences, quadratic reciprocity, Diophantine equations. Introduction to continued fractions and a brief discussion of public key cryptography. Prerequisite: Math 310 or permission of instructor.
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3.00 Credits
Topics change with each offering of the course. Past topics have included Mathematics and Multimedia, Mathematics and Chemistry of Reaction-Diffusion Systems, Mathematical Biology, and Simulation Analysis of Random Processes. Prerequisites vary, but always include at least Math 233 and usually Math 309.
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3.00 Credits
Basics of enumeration (combinations, permutations, and enumeration of functions between finite sets), generating functions; the inclusion-exclusion principle, partition theory, and introductory graph theory. As time permits, additional topics may include Ramsey's Theorem, probabilistic methods in combinatorics and algebraic methods in combinatorics. Prerequisites: Math 132, 309, and 310, or permission of the instructor.
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3.00 Credits
Introduction to graph theory including the basic definitions and theorems and some more advanced topics that drive much current research in graph theory: Ramsey's Theorem, random graph theory and, if time permits, Szemeredi's regularity lemma. Graphs are studied as abstract objects; however, graph theory is also of interest to applied mathematicians because graphs are natural models for networks (social, electric,.). Prerequisite: Math 310 or a roughly equivalent course, or permission of instructor. Students should know what a proof is and how to produce one. Some informal understanding of probability is helpful, but students need not have taken a probability course.
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1.00 - 3.00 Credits
Approval of instructor required.
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3.00 Credits
Same as Phil 403
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3.00 Credits
Same as Phil 404
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