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Course Criteria
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3.00 Credits
A study of the field of complex numbers, elementary functions of a complex variable, limits, derivatives, analytic functions, mapping by elementary functions, integrals, power series, residues and poles.
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3.00 Credits
A study of general topology including applications to Euclidean spaces, surfaces, topological invariants, continuous functions, and homeomorphisms.
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3.00 Credits
An introduction to mathematical techniques used in advanced physics. Topics include Fourier series, special functions, integral transforms, boundary value problems, and partial differential equations.
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3.00 Credits
This course is designed so that prospective teachers can gain a deeper understanding of the key ideas of secondary school mathematics in the areas of number and operations, algebra, geometry, measurement, and data analysis.
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0.00 - 9.00 Credits
A study of modern concepts in special areas of mathematics.
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1.00 - 9.00 Credits
An internship in a service-learning experience based in an institution or agency, emphasizing the completion of a specific task and the acquisition of specific knowledge and skills under the supervision of ASU and the cooperating institution or agency.
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0.00 - 9.00 Credits
Individual mathematics research, a minimum of three hours per week for each semester hour credit.
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3.00 Credits
This course offers an introduction to the basic statistical techniques used to analyze and interpret data in the health sciences and related fields. Emphasis is on applications of these methods, with graphical statistics (estimation and hypothesis testing) for numeric and categorical data, nonparametric methods, analysis of variance, regression, and correlation. MATH 2013 (Grade of C or better).
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3.00 Credits
This course is a study of the general linear statistical model and the linear hypothesis. Topics include the multivariate normal distributions of quadratic forms, and parameter estimation and hypothesis testing for full-rand regression models. Regression diagnostics and "dummy" variable coding will also be covered.
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3.00 Credits
Introduction to the theoretical properties of point estimators and tests of hypotheses, sufficient statistics, likelihood, best linear unbiased estimates, elements of statistical tests, the Neyman Pearson Lemma, UMP tests, univariate normal inference, decision theory and multivariate distributions are covered.
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