Bridges the gap between computational, algorithmic mathematics courses and more abstract, theoretical courses. Emphasizes the structure of modern mathematics: axioms, postulates, definitions, examples conjectures, counterexamples, theorems, and proofs. Builds skill in reading and writing proofs. Includes careful treatment of sets, functions, relations, cardinality, and construction of the integers, and the rational, real, and complex number systems.
Every Fall
Previously: MATH 200
Vector spaces, linear independence, basis and dimension, linear mappings, matrices, linear equations, determinants, Eigen values, and quadratic forms.
Every Spring
Previously: MATH 220
The calculus of vector-valued functions, functions of several variables, and vector fields. Includes vector operations, equations of curves and surfaces in space, partial derivatives, multiple integrals, line integrals, surface integrals, and applications.
Every Spring
Previously: MATH 153
Methods of solving first and second order differential equations, applications, systems of equations, series solutions, existence theorems, numerical methods, and partial differential equations.
Every Fall
Previously: MATH 310
The specific topics of the course include Introduction to Regression Analysis, Straight-Line Regression Analysis, The correlation coefficient and Straight-Line Regression Analysis, The Analysis of Variance table, Multiple Regression Analysis, Statistical Inference in Multiple Regression, Correlations, Confounding and Interaction in Regression, Regression Diagnostics.
Previously: MATH 305