Program Support Course Descriptions

Restricted to Connell School of Nursing students.

This course introduces statistics as a liberal discipline and applies the principles of statistics to problems of interest to health sciences professionals. Students will gain an understanding of statistical ideas and methods, acquire the ability to deal critically with numerical arguments, and gain an understanding of the impact of statistical ideas on the health sciences, public policy and other areas of application.

Restricted to Lynch School of Education students. Satisfies Mathematics Core Requirement.

MT 190-191 is a course sequence designed for those who plan to teach mathematics in grades K-8. The emphasis is on building conceptual understanding of the mathematics present in the emerging K-8 curriculum and on deepening content knowledge. Number and number systems through the real number system will be studied; functions and the structure of algebra will be developed. Problem solving and reasoning, applications, and making connections will be featured.

Restricted to Lynch School of Education students. Satisfies Mathematics Core Requirement.

As in MT 190, the course emphasizes building conceptual understanding of the mathematics present in the emerging K-8 curriculum and on deepening the content knowledge. Topics drawn from geometry and measurement, data analysis, statistics, and probability will be developed. Problem solving and reasoning, applications, and making connections will be featured.

Prerequisite: MT101, MT103, MT105, or MT202. Note: this course does not count as an elective for the Mathematics major. It does count as an elective for the Mathematics minor.

Bioinformatics is concerned with analyses of large biological data sets, primarily genetic. Many of the tools used rely on probability theory and stochastic processes. This course presents some of the background theory needed for these analyses. Topics include sample spaces and events; random variables; discrete and continuous distributions; moments; joint, marginal, and conditional distributions; covariance; conditional expectations; Poisson processes; Markov chains; and hidden Markov models.

Restricted to Carroll School of Management students.

Prerequisites: MT100 Calculus I (or equivalent) and CS021 [MC021] Computers in Management.
Corequisite: EC151 Statistics.

Topics include linear and integer programming, decision analysis, nonlinear optimization, and computer solutions using Excel.

Not open to students who have completed MT445 or MC248 or CS245. Cannot be used for Major credit.

This course is intended for computer science majors and introduces the student to the fundamental notions of discrete mathematics, with an emphasis on graph theory and applications.

Topics include the basic notions of set theory and logic, graphs, equivalence relations and partial orderings, basic counting techniques, finite probability, propositional logic, induction, graphs and trees, paths, circuits and cycles, recursion and recurrence relations, and Boolean algebra.

Prerequisites: MT190 and MT191.

This course is intended to focus on the wealth of topics that relate specifically to the natural numbers. These will be treated as motivational problems to be used in an activity-oriented approach to mathematics in grades K-9. The course will demonstrate effective ways to use the calculator and computer in mathematics education. Topics include prime number facts and conjectures, magic squares, Pascal's triangle, Fibonacci numbers, modular arithmetic, and mathematical art.

Prerequisites: MT190 and MT191.

This course is intended to fill a basic need of all teachers of grades K-9. Geometry now occupies a significant role in the elementary mathematics curriculum. The course will treat content, but ideas for presenting geometry as an activity-based program will also be stressed. Topics to be covered include the geoboard and other key manipulatives, elements of motion and Euclidean geometry, and suggestions for using Logo as a tool to enhance teaching geometry.

Prerequisite: MT202.

MT305 is required for Geology-Geophysics, Geophysics, and Physics majors. It is also recommended for Chemistry majors.

Topics include linear second order differential equations, series solutions of differential equations including Bessel functions and Legendre polynomials, and solutions of the diffusion and wave equations in several dimensions.

Prerequisite: None.

This course is a close reading of Euclid's Elements in seminar style, with careful attention to axiomatic reasoning and mathematical constructions that build on one another in a sequence of logical arguments.

We will also emphasize clear and creative communication on mathematical ideas, with some attention to the cultural background of the Elements and its place in a modern education.

Prerequisites: MT202 Multivariable Calculus, MT210 Linear Algebra, and MT216 Introduction to Abstract Mathematics (or equivalent mathematical background). Permission of the instructor required for students outside the LSOE. 

This course is designed to deepen students' mathematical knowledge through solving, explaining, and extending challenging and interesting problems. Students will work both individually and in groups on problems chosen from polynomials, trigonometry, analytic geometry, pre-calculus, one-variable calculus, probability, and numerical algorithms. The course will emphasize explanations and generalizations rather than formal proofs and abstract properties. Some pedagogical issues, such as composing good problems and expected points of confusion in explaining various topics will come up, but the primary goal is mathematical insight. The course will be of particular use to future secondary math teachers.

Restricted to graduate students in the Interdisciplinary Statistics Minor Program.

This course is an introduction to probability, calculus, and linear algebra for graduate students in the Statistics Minor Program having little or no formal training in these subjects. Topics include: counting methods, axioms and properties of probability, conditional probability, independence, Bayes rule, limits, infinite series, derivative and integral methods, vector and matrix operations, and computer methods. Applications will be emphasized throughout the course.