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Course Criteria
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4.00 Credits
The course covers the application of basic statistical methods such as univariate graphics and summary statistics, basic statistical inference for one and two samples, linear regression (simple and multiple), one- and two-way ANOVA, and categorical data analysis. Students use statistical software to analyze data and conduct simulations. A student who takes Mathematics 209 cannot receive credit for Mathematics 115. Prerequisite: Mathematics 133 or permission of instructor. STAFF.
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4.00 Credits
A unified study of the concepts underlying linear systems and linear transformations and of the techniques for using them. Topics: matrix algebra, rank, orthogonality, vector spaces and dimension, eigenvectors and eigenvalues. Typical applications: fitting lines and curves to data, Markov processes, linear differential equations. Prerequisite: Mathematics 133 or permission of instructor. STAFF
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4.00 Credits
An introduction to the basic objects, numbers, and techniques of combinatorics. Includes combinations, permutations, partitions, and graphs; binomial and other coefficients; inclusion-exclusion, recurrence relations, and generating functions and series. Prerequisite: Mathematics 215 or permission of instructor. E. MOORE, T. MOORE.
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4.00 Credits
First and second order differential equations; series solutions and Fourier series; linear and nonlinear systems of differential equations; applications. Prerequisite: Mathematics 215 or permission of instructor. CHAMBERLAND, SHUMAN.
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1.00 Credits
Students solve challenging mathematics problems and present solutions. Prepares students to take the Putnam Examination, if they wish. Prerequisite: Mathematics 133, or concurrent registration in Mathematics 133, or permission of instructor. May be repeated for credit. S/D/F only. STAFF.
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4.00 Credits
An introduction to the process and techniques of modeling "real-world" situations,using topics from linear algebra and differential equations. Appropriate mathematics, including numerical methods, developed when needed. Models drawn from both the social and natural sciences. Prerequisite: Mathematics 220 or permission of instructor. CHAMBERLAND.
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4.00 Credits
In addition to a short review of hypothesis testing, confidence intervals, and 1-way ANOVA, this course incorporates experiments from several disciplines to explore design and analysis techniques. Topics include factorial designs, block designs (including latin square and split plot designs), random, fixed, and mixed effects models, crossed and nested factors, contrasts, checking assumptions, and proper analysis when assumptions are not met. Prerequisite: Mathematics 209, or 336, or permission of instructor. KUIPER, MOORE.
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4.00 Credits
This course will focus on investigative statistics labs emphasizing the process of data collection and data analysis relevant for science, social science, and mathematics students. These labs will incorporate current events and interdisciplinary research, taking a problem-based approach to learn how to determine which statistical techniques are appropriate. Topics will typically include nonparametric tests, designing an experiment, and generalized linear models. Prerequisite: Mathematics 209, or 306, or permission of instructor. KUIPER.
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4.00 Credits
Topics include, but are not limited to, one of the following: Chaos and Fractals (one- and two-dimensional discrete dynamics, iterated function systems, fractal dimension), Fourier Analysis (fast Fourier transform, Fourier series, wavelets), or Partial Differential Equations (heat and wave equation, eigenfunction expansions). May be repeated for credit. Prerequisite: Mathematics 220 or permission of instructor. STAFF.
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4.00 Credits
A thorough study of the topology of the real line and of limits of functions of one real variable. This theory is then used to develop the theory of the derivative and integral of functions of one real variable and also sequences and series of real numbers and functions. Prerequisite: Mathematics 218, or 220, or permission of instructor. FRENCH, SHUMAN.
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