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The second of a two course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.
The first of a two course sequence of faculty-directed independent research culminating in the writing of a senior thesis and its presentation.
The fundamentals of graph theory: trees, connectivity, Euler torus, Hamilton cycles, matchings, colorings and Ramsey theory.
This course is a problem oriented introduction to the basic concepts of probability and statistics, providing a foundation for applications and further study.
Elementary combinatorial techniques used in discrete problem solving: counting methods, solving linear recurrences, graph and network models, related algorithms, and combinatorial designs.
Functions, the derivative, applications of the derivative, techniques of differentiation, integration, applications of integration to probability and statistics, multidimensional calculus.
Linear equations, matrices, linear programming, sets and counting, probability and statistics.
The topics covered parallel those of MATH 2552 with a somewhat more intensive and rigorous treatment.
Methods for obtaining numerical and analytic solutions of elementary differential equations. Applications are also discussed with an emphasis on modeling.
Linear approximation and Taylor’s theorems, Lagrange multiples and constrained optimization, multiple integration and vector analysis including the theorems of Green, Gauss, and Stokes.
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