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Course Criteria
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4.00 Credits
The course will focus on sampling design, statistical analysis, data collection, and the presentation of results. This is a field-based course that will prepare students to conduct research in ecology using statistical techniques appropriate for ecology. In addition to the nonparametric techniques of bootstrapping and randomization, students will learn the basic multivariate, time series, and spatial statistics employed in ecological analysis. Students will learn how to design sampling strategies, implement basic sampling techniques, collect data efficiently, analyze and present their data. Prereq: MATH 232 or MATH/BIO 233 grade C- or higher, or c/i. (fall)
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4.00 Credits
This course serves as an introduction to mathematics statistics using calculus. Topics to be covered will include random variables, distribution and density functions, joint and conditional distributions, moment generating functions, technique for sums, convergence in distribution, convergence in probability, and the central limit theorem. Prereq: MATH 131 and MATH 202 grade C- or higher, or c/i. (spring/even-numbered years)
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4.00 Credits
Upon successful completion of this course the student should be familiar with deductive and inductive reasoning and with the axioms and theorems of Euclidean and non-Euclidean geometries. The student should exhibit competence in performing geometric constructions both by hand and with the aid of computer software, in proving geometric theorems in both Euclidean and non-Euclidean geometries, and in solving a variety of problems based upon the geometric properties studied. Prereq: MATH 007 grade C- or higher, or c/i. (fall)
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4.00 Credits
Upon successful completion of this course the student should be familiar with both ancient and modern numeration systems, with the contribu-tions to mathematics by famous mathematicians, and with the chrono-logical order of significant events in mathematics. The student should also exhibit competence in solving selected problems using appropriate historical mathematical methods. Prereq: MATH 341 grade C- or higher, or c/i. (fall/odd-numbered years)
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4.00 Credits
Upon successful completion of this course the student should be familiar with techniques of writing mathematical proofs using direct, contra-positive, contradiction, and induction methods. In addition, the student will be introduced to some fundamental ideas used throughout mathe-matics including logic, set theory, number theory, complex numbers, function theory, and group theory. Prereq: Sophomore standing. (fall)
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4.00 Credits
Upon successful completion of this course the student should be familiar with current trends in the methods and materials used for effective teach-ing of mathematics. The student should exhibit competence in developing unit and lesson plans, expository and inquiry-based instruction, forms of professional development, theories of instruction, the appropriate use of technologies in instruction, skills in effective communication with students and peers on mathematical and professional educator topics. Professional education field experience in a school required. Prereq: TEP and MATH 341 grade C- or higher, or c/i. (spring)
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3.00 Credits
This is intended as a culminating course for students who wish to incorporate an appropriate work experience within their academic education. The student will actively participate in a mathematically-related work experience that should provide her/him with an under-standing of how mathematics is applied in industry. Assessment will be by both written and oral consultation with the student's academic advisor. Prereq: Senior standing and c/i.
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4.00 Credits
An introduction to discrete and continuous time models that arise from the study of dynamical systems designed to model phenomena that occur in nature. Difference equation, matrix equation, and ordinary differential equation models will be formulated for a broad range of applications and analyzed both analytically and numerically. Prereq: MATH 202 grade C- or higher, or c/i. (spring/odd-numbered years)
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3.00 Credits
Selected topics under faculty supervision. Prereq: c/i and c/vc. (on demand)
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4.00 Credits
This is a course in stochastic processes with emphasis on model building and probabilistic reasoning. Topics to be covered may include a review of elementary probability theory, Poisson processes, discrete and continuous time Markov chains, Brownian motion, random walks, and martingales. Applications will be drawn from the physical, biological, and social sciences. Students will learn hands-on design and construc-tion of working models using appropriate technology. Upon successful completion of this course the student should be proficient in asking research questions, collecting and arranging data, and designing models to answer the questions asked. Prereq: MATH 131 grade C- or higher, or c/i. (spring/even-numbered years)
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