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Course Criteria
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2.00 Credits
This course is an introduction to modeling time series data using smoothing techniques, regression, and autoregressive models. Estimation, data analysis and forecasting using real data will be examined. Pre-requisite: MA 220
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4.00 Credits
Applications of definite integral and Fundamental Theorem of Calculus, methods of integration, power series, Taylor series, Fourier series, use of differential equations to model real-life applications. Pre-requisite: Mathematics 140
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4.00 Credits
Introduction to calculus of several variables, partial derivatives, multiple and iterated integrals, and vector functions. Pre-requisite: Mathematics 240.
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1.00 - 3.00 Credits
No course description available.
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3.00 Credits
Elements of plane and solid geometry treated from a problem-solving approach, historical development of geometry, parallelism and symmetry, area and volume, and non-Euclidean geometry. Pre-requisite: Mathematics 240.
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3.00 Credits
Matrices, linear systems, finite dimensional vector spaces, vector geometry, linear transformations, quadratic forms. Pre-requisite: Mathematics 240.
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3.00 Credits
Combinatorial analysis, probability axioms, random variables and their distributions including binomial, normal, Student?s t and f, estimation and sampling, hypothesis testing, linear and multivariate regression. Pre-requisite: Mathematics 240.
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3.00 Credits
Elementary differential equations and applications including linear differential equations with constant coefficients and first order systems, higher order differential equations and applications. Existence and uniqueness theorems. Numerical techniques. Pre-requisite: Mathematics 250 and Mathematics 303 or concurrent enrollment.
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3.00 Credits
An introduction to the theory of computation emphasizing formal languages, automata, and computability. Includes computational complexity and NP-completeness. Pre-requisite: Mathematics 208.
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3.00 Credits
Iterative methods for approximating numerical solutions to systems of equations, polynomials, integral and differential equations. Includes matrix manipulation and error analysis. Pre-requisite: Mathematics 240 or consent of instructor.
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