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Course Criteria
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3.00 Credits
Logic, rules of inference, methods of proof including direct and indirect methods, sets, functions, and mathematical relations and properties of relations. Calculus II must be taken prior to or with Math 311.
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3.00 Credits
Materials and methods of teaching mathematics in grades 5-8. Open only to math majors with a concentration in teaching and to elementary education majors with a specialty in mathematics. In addition to those students who have completed the listed prerequisites, students who are majoring in secondary math education and who have Junior standing may take this course.
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3.00 Credits
The purpose of this course is to provide an understanding of the fundamental concept of financial mathematics, and how those concepts are applied in calculating present and accumulated values for various streams of cash flows. Reserving, valuation, pricing, asset/liability management, investment income, capital budgeting and valuing contingent cash flows will be discussed. An introduction to financial instruments and the concept of no-arbitrage as it relates to financial mathematics will be given. This course covers topics of CAS/SOA Actuarial Exam 2/FM.
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4.00 Credits
Calculus of several variables-- partial differentiation, multiple integration, vector calculus, line and surface integrals, Green's Theorem, and Stoke's Theorem. Students must have taken, or be currently enrolled in, Math 260.
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3.00 Credits
Systems of linear equations, Gauss-Jordan elimination, linear programming, matrices, determinants, vector spaces, linear transformations, and eigenvectors.
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4.00 Credits
Probability, probability distributions of discrete random variables, probability density functions, expected value and variance, sampling distributions and central limit theorem, point and interval estimation, and tests of hypotheses for the population mean. Simple linear regression, one factor ANOVA and ANOVA for regression.
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3.00 Credits
This course covers the theory and applications of linear regression models, generalization linear models, tree-based models, autoregressive and forecasting time series models. Topics includes parameter estimations, variables selection, model validation and diagnose, statistical inference and predictions. Student will learn basic R programming language and practically implement the models with real data in the actuarial science contexts. The course covers the topics as required in the Statistics for Risk Modeling (SRM) Exam offered by the Society of Actuaries (SOA) and prepare students for the SRM exam.
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3.00 Credits
Techniques of developing and analyzing mathematical descriptions of physical phenomena.
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4.00 Credits
A rigorous treatment of concepts of calculus and foundations of mathematics including logic and sets, Bolzano-Weierstrass Theorem, limits, Heine-Borel Theorem, continuity, and derivative.
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3.00 Credits
A continuation of the rigorous treatment of concepts of calculus and foundations of mathematics including the Riemann integral, infinite series, sequences of functions and uniform convergence.
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