Intensive study of the problem-solving process. Algebraic, patterning, modeling, and geometric strategies are explored. Includes a review of basic algebra skills and concepts necessary for problem solving. Consent of the Department is required. This does not fulfill the Mathematical Arts requirement of the Sophia Program.

This course will cover topics in algebra that are needed for future courses. Topics will include basic algebraic concepts, linear equations and systems, polynomials, rational functions, absolute values, roots, and linear, polynomial and rational function inequalities.

Mathematical modeling through the use of graph theory. Topics include graphs, directed graphs, trees, matchings and network flows. Designed primarily for first year college students.

This course studies polynomial, rational, exponential, logarithmic, and trigonometric functions from the symbolic, numeric, and graphical perspectives. The emphasis on these concepts will provide solid preparation for a college-level calculus course. This does not fulfill the Mathematical Arts requirement of the Sophia Program. Prerequisite: MATH 101 or recommendation of Math Placement Advisor.

Set theory, counting techniques, probability, random variables, expected value, variance, standard deviation, and linear programming. Prerequisite: MATH 101 or recommendation of Math Placement Advisor.

This course develops and applies mathematical concepts and tools to quantitatively explore sustainability issues. Topics such as industrial agriculture, energy sustainability, population growth, and ecological footprints will be explored from environmental, social, and economic perspectives wherever possible. Mathematical concepts developed in the course are motivated through the study of these topics and allow students to survey several mathematical areas. Particular concepts covered include properties of real numbers, algebraic simplification of expressions, solving equations and inequalities, rates of change, interpretation of numerical information, functions and inverses, modeling, differentiation/integration, qualitative analysis of differential equation models, calculating probabilities, statistical techniques on real data, and graph paths and connectivity.

Matrices, systems of equations, determinants, eigenvalues, linear transformations, complex numbers, orthogonality. Emphasis on applications.

Finite geometries. Transformational geometry with an introduction to fractals. Euclidean geometry, including classical constructions. Non-Euclidean geometries, including hyperbolic and/or projective geometry. Prerequisite: MATH 104 or MATH 105.

A one semester introduction to differential and integral calculus designed primarily for liberal arts students and those in the professional programs. An emphasis on applications and modeling. Prerequisites: MATH 103 or recommendation of Math Placement Advisor.

Introduction to basic sampling and experimental design. Basics of probability, random variables, and probability distributions. Sampling distributions. Estimation and hypothesis testing for means and proportions. Statistical software will be used. Prerequisite: MATH 104, MATH 113, MATH 121, or equivalent.

Problem solving and strategies; properties of whole numbers, integers, rational numbers, and real numbers; algorithms and computation; elementary number theory. The course follows the recommendations of the Mathematical Association of America and the National Council of Teachers of Mathematics for the training of elementary teachers. Prerequisite: One Mathematical Arts Sophia Program course.

How can data empower communities while avoiding harm? In this course, we will explore how data influences critical issues, from efforts to close the gender pay gap to addressing environmental challenges like climate change and renewable energy. Students will engage in hands-on work with real-world data to develop key quantitative skills, including evaluating evidence, interpreting statistical claims, and recognizing biases in data collection. We will investigate how flawed data, misleading statistics, and biased algorithms shape policies and impact marginalized communities. Open to all majors, this course welcomes students of all backgrounds—no advanced math skills required—just a willingness to engage with new ideas and a commitment to understanding how data can drive positive change.

The first course in a two course sequence with MATH 132. The two courses will cover the following topics: algebraic and transcendental functions; limits; continuity; derivatives; maxima and minima; concavity; related rates; Taylor polynomials; Mean Value Theorem; anti-differentiation; Riemann sums; the Fundamental Theorem of Calculus; techniques of integration; sequences and series. The course is based on graphical, numerical, and symbolic points of view. Graphing calculators are used throughout the course. Prerequisite: MATH 103 with a grade of "C" or higher, or recommendation of Math Placement Advisor.

The second course in a two course sequence with MATH 131. The two courses will cover the following topics: algebraic and transcendental functions; limits; continuity; derivatives; maxima and minima; concavity; related rates; Taylor polynomials; Mean Value Theorem; anti-differentiation; Riemann sums; the Fundamental Theorem of Calculus; techniques of integration; sequences and series. The course is based on graphical, numerical, and symbolic points of view. Graphing calculators are used throughout the course. Prerequisite: MATH 131 or recommendation of math placement advisor.

This course is designed for students who have completed a full year of calculus in high school and have mastered the mechanics of differentiation and integration. The basic concepts of a two-semester college calculus sequence, including limits, derivatives, integrals, sequences and series, will be explored in depth. The emphasis of the course is on understanding the theory of calculus and constructing mathematical models. Prerequisite: A minimum score of 4 on the AP Calculus exam, recommendation of Math Placement Advisor, or permission of instructor.

This course in applied math and politics will focus on the mathematics behind voting in both two-party and multi-party systems, comparing systems in the US with those in France and Ireland. Students will explore both implemented and theoretical social choice functions and analyze each, subject to standard criteria. They will develop an understanding for how formal rules and procedures have an impact on policy outcomes and informal institutions such as political parties.

Basic number theoretic concepts are studied, with an emphasis on writing proofs. Divisibility; primes; Euclid’s algorithm and its consequences; linear diophantine equations; residue classes; linear congruences; arithmetic functions. Applications of number theory to computer science (cryptography, complexity of computations). Prerequisite: MATH 118 or MATH 131.

Introduction to basic sampling and experimental design. Basics of probability, random variables, and probability distributions. Sampling distributions. Estimation and hypothesis testing for means and proportions. Statistical software will be used. Prerequisite: MATH 104, MATH 108, MATH 113, MATH 121, or equivalent.

Set theory, logic, relations, functions, and an introduction to abstract mathematical structures, with an emphasis on reading and writing mathematical proofs. Prerequisite: MATH 132 or 133, or permission of instructor.

Three-dimensional space: parametric equations, lines, planes, vectors, dot product, cross product. Polar coordinates. Vector-valued functions. Functions of several variables: partial derivatives, linear approximation, gradient, directional derivatives, maxima, minima, chain rule. Multiple ntegrals. Vector Calculus (including Green’s Theorem and Stokes’ Theorem). Prerequisite: MATH 132 or MATH 133.

Sampling studies, design of experiments, hypothesis testing, analysis of variance, regression and correlation, regression modeling, time series. Introduction to operations research: queuing, systems analysis, quality assurance, acceptance sampling. Emphasis on applications to business and economic decision making. Prerequisite: MATH 114 with a grade of “C” or higher (also listed as BUAD 341).

An introduction to Operations Research—quantitative models used in management decision-making. The course will focus on the models as tools with computer software used extensively for problem solving and assignments. Case studies are used. Prerequisite: One year of Calculus or MATH 114 (also listed as BUAD 427).

Mathematical theory of interest, annuities, amortization schedules, yield rates, and sinking funds. Prerequisite: Two semesters of calculus or equivalent or permission of the instructor.

This course has three major components: an overview of the history of mathematics, the lives and contributions of selected women mathematicians throughout history, and the experiences of women in the contemporary mathematical community. In our general exploration of history, we focus on the development of mathematical ideas and the contributions made by various cultures and individuals. Among the historical figures studied in depth are Hypatia, Maria Agnesi, Sophie Germain, Sofia Kovaleskaia, Emmy Noether, Julia Robinson. The course will examine the ways in which the views of the modern mathematical community and the broader society discourage or encourage the participation of women and other under-represented groups in mathematics. Prerequisite: One semester of college-level calculus or equivalent.

Review of basic properties of the real number system. Foundations of Euclidean geometry with additional study of transformational geometry. Elementary probability and statistics. This course meets for two hours of class instruction and has a two-hour laboratory component. Recommendations of MAA and NCTM are continued. Prerequisite: Two MATH courses including MATH 118 with a grade of C or higher in MATH 118.

Linear systems; linear independence; matrix algebra; determinants; vector spaces including subspaces, dimension, rank, change of bases; linear transformations; eigenvalues and eigenvectors; inner product; orthogonality; and Gram-Schmidt. An introduction to differential equations, including first order linear, separable, and exact; second order with constant coefficients and variation of parameters, reduction of order, and undetermined coefficients. Applications included. Prerequisites: MATH 231.

A study of methods for solving higher order linear ordinary differential equations, linear first order systems, and boundary value problems for the heat and wave equations. Analysis of nonlinear systems of first order ordinary differential equations using approximation by linear systems, numerical solutions and phase portraits. The course will use mathematical software to solve differential equations and systems of differential equations symbolically, numerically and graphically. Prerequisite: MATH 326.

Computer arithmetic and algorithm convergence. Solutions of equations. Optimization. Numerical linear algebra. Numerical solutions to ordinary differential equations. Numerical differentiation and integration. Error analysis. Prerequisite or corequisite: MATH 326.

Introduction to graph theoretic and combinatoric models: planar graphs; circuits; spanning trees; network flows; counting; generating functions; recurrence relations. Prerequisites: MATH 225 and CPSC 207.

Construction of the reals; Sequences; Real valued functions of a single real variable: continuity, uniform continuity, sequences and series of functions, uniform convergence, differentiation, integration. Prerequisites: MATH 225 and MATH 231.

Construction of the reals; Sequences; Real valued functions of a single real variable: continuity, uniform continuity, sequences and series of functions, uniform convergence, differentiation, integration. Prerequisite: MATH 341.

A calculus-based approach to probability theory. Topics include probability spaces, classical theory, random variables, discrete and continuous distributions, multivariant distributions, transformations of random variables, random sampling, the law of large numbers, the central limit theorem and moment generating functions. Prerequisite: MATH 231 or equivalent.

Topics include sampling distributions, estimation, theory of estimators, test of hypotheses, analysis of variance, regression and correlation analysis, time series, experimental design, modeling and decision criteria. The use of statistical analysis in decision problems is stressed. Prerequisite: MATH 345 or equivalent.

Basic algebraic systems: groups, rings, and fields. Homomorphisms and factor groups, rings. Polynomial rings and field extensions. Applications, including symmetry groups and algebraic coding theory. Prerequisite: MATH 225 and MATH 326.

Basic algebraic systems: groups, rings, and fields. Homomorphisms and factor groups, rings. Polynomial rings and field extensions. Applications, including symmetry groups and algebraic coding theory. Prerequisite: MATH 353.

Historical and formal development of Euclidean and non-Euclidean geometries; role of axiom systems; congruence, parallelism, measurement. Prerequisite: MATH 225.

Stochastic models of contingent payment, survival, frequency, severity and ruin. Compound distribution models. Emphasis on application to actuarial models. Prerequisite: MATH 345.

In this course, students study the modeling process with application from difference equations, probability, dynamical systems, optimization, and simulation. Students will design, develop, implement, evaluate, and present mathematical models using real data for observable phenomena. Models and issues related to environmental and sustainability studies are emphasized. Prerequisites: MATH 326 and MATH 345.

We focus on solving problems provided to us by partner organizations in business, industry, or government (BIG). Students develop their technical skills (mathematics, statistics, programming) as well as skills valued by employers of STEM professionals: teamwork, written and oral communication, independent problem solving, and meeting deadlines. This course is based on the PIC Math (Preparation for Industrial Careers in Mathematics) model developed by the Mathematical Association of America. Prerequisites: Math 231 and CPSC 207, or permission of instructor.

Topics in Mathematics not covered in the regular department offerings. May be repeated with a different topic.

The goal of this course is for students to prepare to take the SOA exam FM. The main topics of this course will be in accordance with the current syllabus for the exam as outlined by the SOA.

The goal of this course is for students to prepare to take the SOA exam P. The main topics of this course will be in accordance with the current syllabus for the exam as outlined by the SOA.

Topics include model building; classical optimization; linear programming; non-linear programming. Prerequisite: MATH 231, MATH 326 and junior or senior status.

Topics in Mathematics not covered in the regular department offerings. May be repeated with a different topic.

Student presentation of selected topics. Prerequisite: Permission of the department chair.

Provides properly qualified students with an opportunity for independent study and careful consideration from an advanced standpoint of selected topics in undergraduate mathematics. Prerequisite: Permission of the department chair. May be repeated.

Professional work experience in mathematics or statistics with a business or organization. May be repeated.

This course introduces the student to an integrated spreadsheet application. Topics covered include: cell formulas and built-in functions, formatting, charting, templates, “what-if” analysis, pivot tables, macros and integration of spreadsheet data into a word processor. Graded S/U.

This course includes a brief history of computing, uses of computers in networking and programming, and ethical issues in computing. Students learn to use a database application as they create and manipulate tables, forms, queries, reports, macros and other database objects.

This course explores program development and design with objects; the designs are implemented in a commonly used, current programming language. The emphasis is on designing, writing, and correcting programs. Topics include the internal organization of the computer, procedures and functions, elementary data structures, and techniques of problem solving. No previous experience with computers is required. The course is focused around a weekly two-hour laboratory and provides in-depth programming experience.

A weekly two-hour laboratory and provides in-depth programming experience.

This course is about learning from data in order to gain useful predictions and insights. Using concepts from computer science, mathematics, and statistics, students will learn the necessary skills to manage and analyze data, including exploratory data analysis, statistical inference and modeling, and machine learning. Prerequisites: CPSC 207 (or equivalent) and one semester of calculus (MATH 113 or 131 or equivalent). Includes lab.

This course is designed to deepen a student’s understanding of how a computer works by studying the C programming language and how it interfaces with assembly language. A weekly laboratory provides experience in controlling the behavior of the computer in ways not possible in higher level languages. Topics include computer organization, assemblers, loaders, link editors, and memory management. Prerequisite: CPSC 207 or equivalent.

This introduction to data communications examines the fundamentals of network architecture including layers, protocols, client/server model, file transfers, and other low-level communications issues. Students will experience hands-on internet related programming including web page development using HTML, and CSS. Prerequisites: CPSC 207 or permission of instructor. Includes a lab.

Corequisite CPSC 308

Theory of computer simulation, including applications of discrete models of industrial and management systems. Topics include probability distributions, random number generation, queuing, design, and analysis of simulation experiments. Includes significant use of simulation software. Prerequisites: CPSC 207 and either MATH 114 or MATH 345.

This course introduces the concepts and techniques of structuring data for complex problems, and provides experience in accessing and processing this data. An object-oriented paradigm is used throughout the course. The course is designed especially for students who will choose a career in information technology. Prerequisite: CPSC 207. Includes a lab.

This course includes a study of systems, particularly those which lend themselves to computer representation, a study of systems analysis and design, and the completion of a major systems project done in a team environment. The project will involve the analysis of an actual system problem, the writing of a system proposal to solve the problem, the presentation of the proposal to the users of the system, and the design and construction of a prototype to implement the proposal. Prerequisite: CPSC 207 or permission of instructor.

CPSC 417 lab

Fundamental concepts of database development, in particular data modeling, database design, and database implementation, as well as managing, retrieving, and updating data within a relational database system. Hands-on experience includes use of the Structured Query Language (SQL) to define, construct, and query a database. Students complete a semester-long project done in a team environment. Prerequisite: CPSC 207 or permission of instructor.

Provides properly qualified students with an opportunity for independent study and careful consideration from an advanced standpoint of selected topics in computer science. Departmental approval required. May be repeated.

Professional work experience in computer science with a business or organization. Graded S/U. May be repeated.