2022-2023 Undergraduate General Catalog


300

MATH 305 Applied Regression

The quality of an applied course is measured by how well they can apply the techniques covered in the course to the solution of real problems encountered in their field of study. Consequently, we advocate moving on to new topics only after the students have demonstrated the ability (through testing) to apply the techniques under discussion. In-class consulting sessions, where a case study is presented and the students have the opportunity to diagnose the problem and recommend an appropriate method of analysis, are very helpful in teaching applied regression analysis. This approach is particularly useful in helping students master the difficult topic of model selection and model building and relating questions about the model to real-world questions. 

Credits

3

MATH 310 Differential Equations

Methods of solving first and second order differential equations, applications, systems of equations, series solutions, existence theorems, numerical methods, and partial differential equations.

Credits

3

Prerequisites

MATH 152

MATH 315 Probability and Statistics

Probability as a mathematical system, random variables and their distributions, limit theorems, statistical inference, estimation, decision theory and testing hypotheses.

Credits

3

Prerequisites

MATH 152

MATH 316 Statistical Inference

 This course content develops the basic statistical techniques used in applied fields like engineering, and the physical and natural sciences. Principal topics include point and interval estimation; tests of hypotheses. Applications include one-way classification data and chi-square tests. This course act as a gateway to other higher-level statistical courses like Bayesian Statistics, Statistical Theory, and Design & Experiment. 

Credits

3

Prerequisites

MATH 315

Notes

This course is primarily made up of the statistics (not probability) content in M315 coupled with additional content for Actuaries Exams.

MATH 320 Discrete Structures

Topics to be selected from counting techniques, mathematical logic, set theory, data structures, graph theory, trees, directed graphs, algebraic structures, Boolean algebra, lattices, and optimization of discrete processes.

Credits

3

Prerequisites

MATH 151; COSC 210

MATH 327 Mathematical Foundations of Data Science

This course explores the mathematical foundations of algorithms used in the field of Data Science, typically taken after a course in mathematical statistics. It includes the study of classification and regression techniques, robust regression, decision trees, support vector machines, neural networks, cross-validation techniques, forecasting models, and Topological data analysis. The course includes a data-driven project that requires the student to propose a question and gather, clean, and analyze data to present a response to a real-world problem.

Credits

3

Prerequisites

MATH 315; COSC 210; COSC 212

MATH 330 History of Mathematics (W)

The history of mathematics from ancient to modern times. The mathematicians, their times, their problems, and their tools. Major emphasis on the development of geometry, algebra, and calculus.

Credits

3

Prerequisites

MATH 200

MATH 335 Modern Geometry

A review of Euclidean geometry, an examination of deficiencies in Euclidean geometry, and an introduction to non-Euclidean geometrics. Axiomatic structure and methods of proof are emphasized.

Credits

3

Prerequisites

MATH 200

MATH 340 Abstract Algebra

A survey of the classical algebraic structures taking an axiomatic approach. Deals with the theory of groups and rings and associated structures, including subgroups, factor groups, direct sums of groups or rings, quotient rings, polynomical rings, ideals, and fields.

Credits

3

Prerequisites

MATH 200; MATH 220

MATH 345 Topology

An introduction to topological structures from point-set, differential, algebraic, and combinatorial points of view. Topics include continuity, connectedness, compactness, separation, dimension, homeomorphism, homology, homotopy, and classification of surfaces.

Credits

3

Prerequisites

MATH 200; MATH 220

MATH 350 Real Analysis

This course develops the logical foundations underlying the calculus of real-valued functions of a single real variable. Topics include limits, continuity, uniform continuity, derivatives and integrals, sequences and series of numbers and functions, convergence, and uniform convergence.

Credits

3

Prerequisites

MATH 200; MATH 220

MATH 355 Complex Analysis

A study of the concepts of calculus for functions with domain and range in the complex numbers. The concepts are limits, continuity, derivatives, integrals, sequences, and series. Topics include Cauchy-Riemann equations, analytic functions, contour integrals, Cauchy integral formulas, Taylor and Laurent series, and special functions.

Credits

3

Prerequisites

MATH 200; MATH 220

MATH 397 TOPICS

Topics in Mathematics.

Credits

3