To view course descriptions scroll down to the desired entry. Statistics courses are listed after Mathematics courses. You may also view Computer Science course listings.
MATH 110 Concepts of Mathematics An introduction to significant ideas of mathematics, intended for students who will not specialize in mathematics or science. Topics are chosen to display historical perspective, mathematics as a universal language and as an art and the logical structure of mathematics. This course is intended for non-majors; it does not count toward either the major or minor in mathematics and students who have passed a calculus course (Math 135, 136 or 205) may not receive course credit for Math 110. Fulfills the distribution requirement in Quantitative Literacy (QLR). Typically offered every semester.
MATH 123 Mathematics and Art This course explores the connections between mathematics and art: how mathematics can provide a vocabulary for describing and explaining art, how artists have used mathematics to achieve artistic goals, and how art has been used to explain mathematical ideas. This course is intended for non-majors; it does not count toward either the major or minor in mathematics. Fulfills the distribution requirement in Quantitative Literacy (QLR). Offered occasionally.
MATH 134 Precalculus A development of skills and concepts necessary for the study of calculus. Topics include the algebraic, logarithmic, exponential and trigonometric functions; Cartesian coordinates and the interplay between algebraic and geometric problems. This course is intended for students whose background in high school was not strong enough to prepare them for calculus; it does not count for distribution credit or for the major or minor in mathematics. Students who have passed a calculus course (Math 135, 136 or 205) may not receive course credit for Math 134. Offered in fall semester only. Fulfills the distribution requirement in Quantitative Literacy (QLR). Offered in the Fall semester.
MATH 135 Calculus I The study of differential calculus. The focus is on understanding derivatives as a rate of change. Students also develop a deeper understanding of functions and how they are used in modeling natural phenomena. Topics include limits; continuity and differentiability; derivatives; graphing and optimization problems; and a wide variety of applications. Fulfills the distribution requirement in Quantitative Literacy (QLR). Offered every semester.
MATH 136 Calculus II The study of integral calculus. Topics include understanding Riemann sums and the definition of the definite integral; techniques of integration; approximation techniques; improper integrals; a wide variety of applications; and related topics. Prerequisite: Math 135 or the equivalent. Fulfills the distribution requirement in Quantitative Literacy (QLR).
MATH 205 Multivariable Calculus This course extends the fundamental concepts and applications of calculus such as differentiation, integration, graphical analysis and optimization, to functions of several variables. Further topics include the gradient vector,parametric equations and series. Prerequisite: Math 136 or the equivalent. Offered every semester.
MATH 206 Vector Calculus A direct continuation of Math 205, the main focus of this course is the study of smooth vector fields on Euclidean spaces and their associated line and flux integrals over parameterized paths and surfaces. The main objective is to develop and prove the three fundamental integral theorems of vector calculus: the Fundamental Theorem of Calculus for Line Integrals, Stokes' Theorem and the Divergence Theorem. Prerequisite: Math 205. Offered every semester.
MATH 217 Linear Algebra A study of finite dimensional linear spaces, systems of linear equations, matrices, determinants, bases, linear transformations, change of bases and eigenvalues. Offered every semester.
MATH 230 Differential Equations An introduction to the various methods of solving differential equations. Types of equations considered include first order ordinary equations and second order linear ordinary equations. Topics may include the Laplace transform, numerical methods, power series methods, systems of equations and an introduction to partial differential equations. Applications are presented. Prerequisite: Math 136. Usually offered every semester.
MATH 250 Mathematical Problem Solving Students meet once a week to tackle a wide variety of appealing math problems, learn effective techniques for making progress on any problem, and spend time writing and presenting their solutions. Participation in the Putnam mathematics competition in early December is encouraged but not required. This course is worth 0.25 credits, meets once per week and is graded pass/fail. Since topics vary from semester to semester, students may repeat this course for credit. Offered occasionally.
MATH 280 A Bridge to Higher Mathematics This course is designed to introduce students to the concepts and methods of higher mathematics. Techniques of mathematical proof are emphasized. Topics covered include logic, set theory, relations, functions, induction, cardinality, and others selected by the instructor. Offered every semester.
MATH 302 Symbolic Logic Offered Through the Philosophy Department. A study of elementary symbolic logic. Topics include sentential and predicate logic. Prerequisite: Philosophy 202 or Mathematics 280 or permission of instructor. Also offered as CS 302 and Philosophy 302. Offered every other year.
MATH 305 Real Analysis A rigorous introduction to fundamental concepts of real analysis. Topics may include: sequences and series, power series, Taylor series and the calculus of power series; metric spaces, continuous functions on metric spaces, completeness, compactness, connectedness; sequences of functions, pointwise and uniform convergence of functions. Prerequisites: Math 205 and Math 280. Offered fall semester.
MATH 306 Complex Analysis Topics include algebra, geometry and topology of the complex number field, differential and integral calculus of functions of a complex variable. Taylor and Laurent series, integral theorems and applications. Prerequisites: Math 205 and Math 280. Offered in the Spring semester.
MATH 315 Group Theory An introduction to the abstract theory of groups. Topics include the structure of groups, permutation groups, subgroups and quotient groups. Prerequisite: Math 280. Offered in the Spring semester.
MATH 316 Ring Theory An introduction to the abstract theory of algebraic structures including rings and fields. Topics may include ideals, quotients, the structure of fields, Galois theory. Prerequisite: Math 280. Offered in the Fall semester.
MATH 318 Graph Theory Graph theory deals with the study of a finite set of points connected by lines. Problems in such diverse areas as transportation networks, social networks, and chemical bonds can be formulated and solved by the use of graph theory. The course includes theory, algorithms, applications and history. Prerequisite: Math 217 or 280. Also offered as CS 318.
MATH 319 Geometry This course presents a selection of results from Euclidean geometry, such as the Euler line, the nine-point circle, and inversion. Students will explore these topics dynamically using geometric construction software. A portion of the course is also be devoted to non-Euclidean geometry, such as spherical, projective, or hyperbolic geometry. The course is especially recommended for prospective secondary school teachers. Prerequisite: Math 217 or Math 280.
MATH 321 Financial Mathematics An introduction to the modern mathematics of finance. This course develops the mathematics necessary in an arbitrage-free model to understand the connections and pricing of stocks, bonds, futures, forwards and a variety of derivatives and options. The course derives the Capital Asset Pricing Model for portfolio optimization, and covers the theory behind the Black-Scholes model for pricing options. Prerequisites MATH 205 or MATH 280.
MATH 323 History of Mathematics This course is offered as a seminar. Primarily for juniors and seniors. Prerequisite: permission of instructor. Offered occasionally.
MATH 325 Probability This course covers the theory of probability and random variables, counting methods, discrete and continuous distributions, mathematical expectation, multivariate random variables, functions of random variables and limit thorems. Prerequisites Math 205. Also offered through Statistics as STAT 325. Offered in the Fall semester only.
MATH 333 Mathematical Methods of Physics Important problems in the physical sciences and engineering often require powerful mathematical methods for their solution. This course provides an introduction to the formalism of these methods and emphasizes their application to problems drawn from diverse areas of classical and modern physics. Representative topics include the integral theorems of Gauss and Stokes, Fourier series, matrix methods, selected techniques from the theory of partial differential equations and the calculus of variations with applications to Lagrangian mechanics. The course also introduces students to the computer algebra system Mathematica as an aid in visualization and problem-solving. Prerequisites: Math 205 and Physics 152. Also offered as Physics 333. Offered in the Fall semester only.
MATH 341 Number Theory The theory of numbers addresses questions concerning the integers, such as “Is there a formula for prime numbers?” This course covers the Euclidean algorithm, congruences, Diophantine equations and continued fractions. Further topics may include magic squares, quadratic fields or quadratic reciprocity. Prerequisite: Math 217 or Math 280 or permission of the instructor. Offered occasionally.
MATH 370 Topology An introduction to topology. Topics may include the general notion of a topological space, subspaces, metrics, continuous maps, connectedness, compactness, deformation of curves (homotopy) and the fundamental group of a space. Prerequisite: Math 280. Offered Occasionally.
MATH 380 Theory of Computation The basic theoretical underpinnings of computer organization and programming. Topics include the Chomsky hierarchy of languages and how to design various classes of automata to recognize computer languages. Application of mathematical proof techniques to the study of automata and grammars enhances understanding of both proof and language. Prerequisites CS 319 and Math 280. Also offered as CS 380. Offered every other year.
MATH 389/390 Independent Projects Permission required.
MATH 450 SYE: Senior Seminar Permission required.
MATH 489 SYE: Senior Project for Majors Permission required.
MATH 498 SYE: Seniors Project For Majors Permission required.
STAT 113 Applied Statistics An introduction to statistics with emphasis on applications. Topics include the description of data with numerical summaries and graphs, the production of data through sampling and experimental design, techniques of making inferences from data such as confidence intervals and hypothesis tests for both categorical and quantitative data. The course includes an introduction to computer analysis of data with a statistical computing package. Fulfills the distribution requirement in Quantitative Literacy (QLR). Offered every semester.
NEW STAT 201 Introduction to Statistical Computing
An introduction to the core ideas of programming through the use of the statistical programming language and software, R. Assumes no prior knowledge of programming but a familiarity with basic statistics is required. The course focuses on building essential programming skills such as objects, data structures and management, functions, and flow control to assist in statistical analyses and will introduce students to the powerful graphing capabilities of R. Additional software platforms will be covered at the discretion of the instructor.
STAT 213 Application Regression Analysis A continuation of STAT 113 intended for students in the physical, social or behavioral sciences. Topics include simple and multiple linear regression, model diagnostics and testing, residual analysis, transformations, indicator variables, variable selection techniques, logistic regression and analysis of variance. Most methods assume use of a statistical computing package. Prerequisite: STAT 113. Offered every semester.
STAT 226 Statistical Methods of Data Collection An introduction to the statistical design and analysis of experiments. This course covers the basic elements of experimental design, including randomization, blocking and replication. Topics will include completely randomized design, randomized complete block design Latin Square and fractorial designs. Analysis of variance techniques for analyzing data collected using these methods is extensively discussed. Additional topics in survey sampling are covered as time allows. Thorough use of statistical software package is incorporated. Prerequisite: STAT 113. Offered in the Fall semester.
NEW STAT 240 Introduction to Statistical Learning
This course is intended to introduce students to a variety of tools and methods in statistical learning. Topics may include supervised learning (such as regression, discriminant analysis, and decision trees), cluster analysis (including hierarchical, k-means, k-mediods, and model based clustering), principal components analysis, and factor analysis. The emphasis will be on applying procedures to data and interpreting both numerical and graphical results
STAT 325 Probability This course covers the theory of probability and random variables, counting methods, discrete and continuous distributions, mathematical expectation, multivariate random variables, functions of random variables and limit thorems. Prerequisites Math 205. Also offered through Mathematics as MATH 325. Offered in the fall semester.
STAT 326 Mathematical Statistics This course deals with the theory of parameter estimation, properties of estimators, and topics of statistical inference including confidence intervals, tests of hypotheses, simple and multiple linear regression, and analysis of variance. Prerequisite: STAT 325. Offered in the Spring semester.
STAT 343 Time Series Analysis Statistical methods for analyzing data that vary over time are investigated. Topics include forecasting systems, regression methods, moving averages, exponential smoothing, seasonal data, analysis of residuals, prediction intervals and Box-Jenkins models. Application to real data, particularly economic data, is emphasized along with the mathematical theory underlying the various models and techniques. Prerequisite: Math 136. Also offered as Economics 343.
STAT 389/390 Independent Projects Permission required.
STAT 450 SYE: Senior Seminar Permission required.
STAT 489 SYE: Senior Project for Majors Permission required.
STAT 498 SYE: Seniors Project For Majors Permission required.