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Course Criteria
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3.00 Credits
Linear and nonlinear equations and functions, exponential and logarithmic functions, simple and compound interest, annuities, matrices and simultaneous equations, sets, introduction to calculus. Fall, Spring [9/4/1996]
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3.00 Credits
Collection and presentation of data, descriptive measures, sets, probability theory, random variables, mathematical expectations, discrete and continuous probability distributions, including Binomial, Poisson and Normal, sampling distributions, introduction to regression and correlations. Fall, Spring [7/1/1996]
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3.00 Credits
Estimation, Type I and II errors, testing of hypotheses, analysis of variance, regression and correlation, time series analysis, index numbers, parameter and interval estimation. Fall, Spring [9/4/1996]
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3.00 Credits
Slope, equations of lines, plane analytic geometry, slope of a curve, rate of change of functions, derivatives of algebraic and trigonometric functions, maxima and minima, mean value theorem, indeterminate forms. [9/4/1996]
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3.00 Credits
Slopes and linear functions, other functions and models, limits and continuity, average rates of change, Instantaneous rates of change in business and economics, differentation techniques, maxima and minima values used in graphing and their application to business and economics, inventory cost and marginal analysis, and introduction to integration. [6/16/2004]
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3.00 Credits
Differentiation and integration of transcendental functions, methods of integration, indeterminate forms, infinite series. Taylor series. Conic sections. [7/1/1996]
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3.00 Credits
Lines and planes in 3-space. Vectors, functions of several variables, partial derivatives, multiple integrals, line integrals, vector analysis. [9/4/1996]
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3.00 Credits
First order linear differential equations, linear differential equations with constant coefficients, variation of parameters, undetermined coefficients, Laplace transforms, solutions in terms of power series, numerical solutions with predictor- corrector and Runge-Kutta methods. [7/1/1996]
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3.00 Credits
This is an in-lab SAS programming course, including importing and exporting files, predictive data modeling and exploration (mixed models analyses, mutivariate statistical analysis, longitudinal analysis, and survival analysis), and a programming approach to report writing. [1/26/2004]
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3.00 Credits
Logic, sets, functions, algorithms. Integers, induction and recursion. Relations, posits, equivalence relations, digraphs and matrix representations. Boolean algebra, applications to logic, Boolean identities, Boolean functions, minimization of circuits. Graphs. Trees. [9/4/1996]
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