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Course Criteria
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3.00 Credits
Prerequisite(s) or Corequisite(s): MATH 2010 and MATH 2800. An introduction to Euclidean and non-Euclidean geometries, emphasizing the distinction between the axiomatic characterizations, and the transformational characterizations of these geometries. Some history of the development of the discipline will also be included.
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3.00 Credits
Prerequisite(s): MATH 2110 and 2800. Elements of point set topology, limits and continuity, differentiability, Taylor's theorem, approximation, Riemann integral. Fall
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3.00 Credits
Prerequisite(s): MATH 4217. Infinite sequences and series, power series, real-valued functions of several variables, vector-valued functions of several variables, implicit function theorem, integral of multivariate functions. Spring
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3.00 Credits
Prerequisite(s): MATH 1920 and MATH 2010. Floating point arithmetic and error propagation, numerical solution to functions of a single variable and functional approximation, numerical differentiation and integration, program design, coding, debugging, and execution of numerical procedures. Fall
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3.00 Credits
Prerequisite(s): MATH 1920 and 2010. Direct and iterative techniques for solving systems of linear equations, curve fitting, and eigenvalue-eigenvector methods. Spring
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3.00 Credits
Prerequisite(s): MATH 1530, MATH 2050, MATH 4047, or permission of instructor. An applied course in statistical methods with emphasis on the selection of an appropriate method, the required assumptions, and applications using statistical software. Comparison of two groups by parametric, nonparametric, and computer intensive methods. Analysis of variance (ANOVA), multiple regression, tests for two-way tables, odds ratio, and relative risk logistic regression. This course is recommended for graduate students from other disciplines who wish to apply statistics and to math majors interested in statistical applications and consulting.
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3.00 Credits
Prerequisite(s): MATH 1530, or 2050, or 4047, or permission of instructor. Topics to be selected from survey designs, simple random, stratified and systematic sampling, questionnaire construction, interviewing techniques, methods of estimation and costs.
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3.00 Credits
Prerequisite(s): MATH 2050 or equivalent. Methods for analysis of observations taken at equally spaced moments in time. Exploratory analysis of time series, decomposition approach, exponential smoothing and regression, time domain approach (ARIMA models), forecasting, introduction to the frequency domain approach, periodogram, and spectrum.
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3.00 Credits
Prerequisite(s): MATH 1920 and MATH 2010. Complex numbers and their algebra, complex differentiation and integration, analytic and elementary functions, residues and power series.
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3.00 Credits
Prerequisite(s): MATH 2800. Topics include graph theory and applications, trees, planar graphs, graphical invariants, and networks. Spring
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