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Course Criteria
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3.00 Credits
Introduction to the study of matrices, linear systems, determinants, eigenvalues, and the geometry of linear operators. Topics from Euclidean n-space include linear transformations, linear independence, span, bases, inner product, and vector spaces. An introduction to structural proof techniques will be a part of the key concepts for the course.
Prerequisite:
MATH 212 (Grade of C or Higher) or MATH 225 (Grade of C or Higher)
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3.00 Credits
This is the second semester of a two-semester sequence in Data Science. Using real-world examples of wide interest and a popular programming language such as R or Python, we introduce methods for key facets of a data-driven investigation. These may include using statistical inference to infer properties of a population, using regression analysis to estimate the relationship among variables, using machine learning to make predictions, and creating interactive data products.
Prerequisite:
MATH 219 (Grade of C or Higher)
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3.00 Credits
Introduction to abstract algebraic structures and formal mathematical proof. Structures may include groups, rings, or fields.
Prerequisite:
MATH 225 (Grade of C or Higher)
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3.00 Credits
Study of first order differential equations. Topics include modeling with differential equations, initial value problems, first and second order linear differential equations, systems of linear differential equations and numerical methods, as well as material chosen from the following topics: Laplace transforms, advanced numerical methods, and partial differential equations.
Prerequisite:
MATH 212 (Grade of C or Higher)
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3.00 Credits
Study of construction of mathematical models to solve real world problems. Entire modeling process from construction of the model, fitting data to the model, analysis, and verification of the model covered. Both continuous and discrete models examined. Examples taken from a variety of disciplines. If prerequisite courses are not met instructor approval is required.
Prerequisite:
MATH 212 (Grade of C or Higher) or MATH 318 (Grade of C or Higher)
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3.00 Credits
Rigorous treatment of foundations of Euclidean geometry and an introduction to spherical and hyperbolic geometries. Topics may include transformational geometry, coordinate geometry, congruence, similarity and constructions. Also provides an historical development of attempts made through the centuries to clarify and expand upon the geometric axioms.
Prerequisite:
MATH 225 (Grade of C or Higher)
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4.00 Credits
Course topics will include basic probability rules, conditional probability and independence, Bayes? rule, discrete and continuous random variables, joint distributions, expectation and variance, probability distributions to include binomial, geometric, hypergeometric, Poisson, Gaussian, exponential, lognormal, t, F, and Chi-square, correlation and covariance, Central Limit Theorem and sampling distributions, simple linear regression, and inference procedures for means and proportions. A statistical software package will be used throughout the course. This class is NOT OPEN to students who have successfully passed MAT 217.
Prerequisite:
MATH 211
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1.00 - 3.00 Credits
Opportunity to offer courses in areas of departmental major interest not covered by the regular courses.
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3.00 Credits
Contact the department for further information on internships.
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3.00 Credits
Contact the department for further information on internships.
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