Department of Mathematics and Computer Science

Associate Professor: Brooke M. Andersen (Chairperson); Assistant Professors: Joseph A. Alfano, Kyle Evans, Bang Tran; Professors of Practice: Raymond Albert, Suzanne L. Kozak, Selvan Snow; Lecturers: Rick Cehon, Kwabena Debrah, Muskan Garg, Dana James, Jean-Marie Johnson, Robert Kumar, Annette Lemerise, Jun Thomas Ma, Karen McGrail.

Computer Science

Mission Statement

The Computer Science program at Assumption University serves all students interested in computer science, computers, and their applications in a supportive and stimulating learning environment. As the science of computer technology, we support the liberal arts mission of the university. As a source of computing skills, we offer courses supporting the development of technical proficiency. For those students who become majors or minors in computer science, we seek to develop their programming skills, their knowledge of computer hardware and software, and an appreciation of the social and ethical implications of technology. The major provides a foundation for a variety of professional careers in the computer industry and for graduate study in computer science.

Cybersecurity

Mission Statement

The mission of the Cybersecurity degree program is to educate the next generation of cybersecurity professionals and leaders. Cybersecurity students develop a strong foundation of professional ethics, critical thinking, and interpersonal communication, as well as acquire the knowledge and technical ability to prevent, detect, respond, and recover from cybersecurity attacks. The program prepares students for employment in cybersecurity and related fields or further graduate level studies. Cybersecurity graduates recognize their responsibility to perform their jobs ethically and with integrity, thereby helping to secure, develop, and sustain the cyberspace ecosystem.

Learning Goals

Cybersecurity program graduates will be able to:

Apply knowledge of computing and information technologies and use software development and security analysis tools to produce effective designs and solutions for specific cybersecurity problems within a variety of computing platforms and employing an approved secure systems development process model;
Identify, analyze, and synthesize scholarly and professional literature relating to the fields of cybersecurity, information security, or information assurance, to help solve specific problems and to stay abreast of the rapidly changing security context;
Participate as an active and effective member of a project team engaged in achieving specific computer-based cybersecurity results or solutions;
Communicate, both orally and in writing, and negotiate with colleagues and other stakeholders including employees, managers, and executives within and between organizations;
Demonstrate sensitivity to and sound judgment on ethical issues as they arise in cybersecurity and will adhere to accepted norms of professional responsibility;
Integrate their technical expertise with knowledge from other disciplines, such as computer science, data analytics, economics, management science, psychology and human factors, to arrive at practical cybersecurity solutions that are effective in real organizations;
Use appropriate tools to prevent, detect, respond, and recover from cyberattacks.

Mathematics

Mission Statement

The Mathematics program provides a supportive and stimulating learning environment to all students interested in the pursuit of truth through mathematics and its applications. As mathematics is a founding discipline of the liberal arts, we support the mission of the University in the Catholic liberal arts tradition, forming students intellectually, through our course offerings in the Foundations Program. As mathematics is the language of science and quantitative analysis, we offer courses for majors in the sciences and business studies. For those students who become majors or minors in mathematics, we seek to strengthen their problem-solving skills, their reasoning and communication abilities, and their knowledge of the various fields of mathematics. The major provides a foundation for meaningful professional careers (including actuarial and engineering sciences, teaching, and business) and for graduate study in a variety of fields.

Learning Goals

Mathematics program graduates will be able to

Communicate mathematical ideas and present mathematical arguments both in writing and orally using proper use of mathematical notation and terminology;
Demonstrate problem-solving proficiency across a wide variety of mathematical and real-world problems;
Write, understand and critique mathematical proofs utilizing correct mathematical terminology and rules of logic;
Know and apply the fundamental principles underlying the major areas of mathematics.

Teacher Preparation

Students interested in the major in Education should consult with the Chairperson of the Mathematics Department and the Licensure Program Coordinator in the Education Department to plan a course of study. Middle school (5–8) and secondary school (8–12) teacher of mathematics programs require a Major in Mathematics. The required courses for the major and the following elective courses address the subject matter knowledge prescribed by the Massachusetts Department of Education for the field of licensure.

MAT 204 Number Theory (8–12)
MAT 208 Probability Theory (8–12)
MAT 351 Modern Algebra I (8–12)
MAT 353 Advanced Euclidean Geometry (5–8, 8–12)
ECO 115 Statistics with Excel OR PSY 224 Statistics (5–8, 8–12)

Actuarial Science

Students interested in becoming an Actuary after graduation should major in Mathematics and take the following electives to prepare for the Actuary Exam:

MAT 207 Actuarial Mathematics
MAT 208 Probability Theory, followed by Exam P
MAT 332 Real Analysis
MAT 355 Differential Equations

Students may be interested in completing a minor in Finance and Data Analytics in addition to the math major to better prepare for their future career. There are many overlapping courses between the major and these minors. Mathematics majors with interest in Actuarial Science are encouraged – but not required – to take the first Actuarial Exam (Exam P, Probability, sponsored by Society of Actuaries) soon after taking MAT 208. Exam P is a minimum requirement for entry into a summer internship or full-time employment as an actuary in an insurance company program. Advanced students may also consider taking the second Actuarial Exam (Exam FM, Financial Mathematics) before graduation. More information about the Actuarial Exam is available at the Society of Actuaries web site: https://www.soa.org Professor Joe Alfano conducts review sessions for students interested in taking the Actuary Exam. Contact him, jalfano@assumption.edu

Engineering Programs with University of Notre Dame and Washington University in St. Louis

Students interested in pursuing either the 3:2 engineering program at Notre Dame, or the 3:3 engineering program with Washington University in St. Louis should take the technical courses listed below in their first year at Assumption. Careful planning is important to meet the prerequisites for admission to Notre Dame or Washington University. Interested students should meet with the dual degree engineering program director, Professor Teresa Herd, to start planning their curriculum.

AU Major	UND/WUSTL Engineering Major	Recommended First-Year Courses at Assumption
AU Major	UND/WUSTL Engineering Major	Fall	Spring
Biology	Biomedical	MAT 117 OR MAT 131H Calculus I CHE 131 Chemistry I BIO 160 Concepts in Biology	MAT 118 OR MAT 132H Calculus II CHE 132 Chemistry II BIO 210 Genetics PHY 213 Introduction to Engineering Problem Solving
Chemistry	Chemical	MAT 117 OR MAT 131H Calculus I CHE 131 Chemistry I BIO 160 Concepts in Biology	MAT 118 OR MAT 132H Calculus II CHE 132 Chemistry II PHY 213 Introduction to Engineering Problem Solving
Environmental Science	Environmental	MAT 117 OR MAT131H Calculus I CHE 131 Chemistry I ENV 150 Introduction to Environmental Science	MAT 118 OR MAT132H Calculus II CHE 132 Chemistry II PHY 213 Introduction to Engineering Problem Solving BIO 160 Concepts in Biology
Math	Aerospace	MAT 117 OR MAT 131H Calculus I PHY 201H Physics I CSC 120 Statistics Programming in Python	MAT 118 OR MAT 132H Calculus II PHY 202H Physics II PHY 213 Introduction to Engineering Problem Solving
	Civil
	Electrical
	Mechanical
	Data Science	MAT 117 OR MAT131H Calculus I PHY 201H Physics I CSC 120 Statistics Programming in Python	MAT 118 OR MAT132H Calculus II PHY 202H Physics II PHY 213 Introduction to Engineering Problem Solving CSC 233 Large Data Sets
	Systems	MAT 117 OR MAT131H Calculus I PHY 201H Physics I CSC 117 Introduction to Programming	MAT 118 OR MAT132H Calculus II PHY 202H Physics II PHY 213 Introduction to Engineering Problem Solving CSC 250 Intermediate Programming
Computer Science	Computer	MAT 117 OR MAT131H Calculus I PHY 201H Physics I CSC 117 Introduction to Programming	MAT 118 OR MAT132H Calculus II PHY 202H Physics II PHY 213 Introduction to Engineering Problem Solving CSC 250 Intermediate Programming

Programs of Study

Major in Computer Science (15 Courses),

Major

Major in Cybersecurity (14 Courses),

Major

Major in Mathematics (12 Courses),

Major

Major in Mathematics with Elementary Education Track (10 Courses),

Major

Minor in Computer Science (8 Courses),

Minor

Minor in Cybersecurity (6 Courses),

Minor

Minor in Data Analytics (6 Courses),

Minor

Minor in Mathematics (6 Courses),

Minor

Courses

CSC 113: INTRODUCTION TO COMPUTER SCIENCE

Credits 3

This course presents an overview of computers and their applications. Students are exposed to a variety of platforms (e.g. MAC, PC, etc.). Topics include popular applications as well as hardware, software, the Internet, social implications and multimedia. Not open to those who have taken CSC 117. (Intersession)

CSC 117: INTRODUCTION TO PROGRAMMING

Credits 3

The goal of this course is to equip students with fundamental problem-solving skills with a high-level, modern programming language (e.g., Python). The emphasis is not on mastering a specific programming language but developing principles of computational thinking, algorithm design, and logical reasoning. These foundational skills enable students to address real-world problems effectively and prepare them for more advanced computer science courses. Topics covered include: representing information (numeral systems, logic circuits, Von Neumann architecture); basic data types, input/output, flows control, collection data types, and procedural programming (including defining functions, using libraries, and recursion).

CSC 120: STATISTICS PROGRAMMING

Credits 3

This course introduces the Python programming language and the R programming language for statistical computing. Students will gain proficiency in writing computer programs to solve basic problems in data analysis. Applied problems will be chosen from a wide variety of subject areas.

CSC 130: DATA VISUALIZATION

Credits 3

This course introduces computer-based techniques for the visual display of quantitative information. Students will gain proficiency in the use of Excel, Tableau, and R to produce effective data visualizations and information graphics.

CSC 175: DATABASES AND SPREADSHEETS

Credits 3

This course covers the establishment and effective use of a database using Access: design, screen forms and data-entry, queries, updating, linking related tables, report generation, and export/import to other programs. It also presents the design and application of spreadsheets using Excel: formatting, ranges, built-in functions, user-defined formulas, array formulas, table-lookups, summaries by pivot tables, graphing, linking, and macros. Some mathematical background is assumed.

CSC 231: COMPUTER ARCHITECTURE

Credits 3

A course introducing the student to computer architecture and assembly language programming. Topics will include memory and addressing, data representation, real and integral arithmetic, instruction formats and sets, indexing, subroutines, and error correction.

CSC 233: LARGE DATA SETS

Credits 3

This course gives the student a detailed introductory experience in skills required for performing data analytics. These skills may include, but are not limited to: data extraction and import; data tidying and transformation; data visualization for exploratory analysis; constructing statistical models from the data; assessing and improving the models; and communicating the results. The programming language, e.g. R or Python, is determined by the instructor.

CSC 250: INTERMEDIATE PROGRAMMING

Credits 3

This course advances the computer programming concepts introduced in the introductory programming course. Its goal is to enhance programming skills in a high-level language (e.g., Python) through more complex coding challenges. The course focuses on programming paradigms, algorithm development, and structured software design. Key topics include advanced control structures and recursion, object-oriented programming principles (encapsulation, inheritance, polymorphism), the application of data structure libraries (e.g., lists, dictionaries, stacks, and queues) to solve real-world problems, as well as debugging and error-handling techniques.

CSC 260: COMMAND LINE INTERFACES

Credits 3

This course introduces a command language computing environment, the bash shell interface to the Linux operating system. Topics covered include: an exploration of the bash shells, hierarchical file structure, file permissions, multiuser systems, utilities, shell scripts, I/O redirection, pipes, and programming in C++.

CSC 261: SIMULATION

Credits 3

Exposition of basic ideas of digital computer simulation of stochastic processes, and the application of those ideas to practical problems such as inventory, queueing, shipping and manufacturing.

CSC 299: SPECIAL TOPICS IN COMPUTER SCIENCE

Credits 3

This course will explore a contemporary computer science topic based on the interest of the professor and needs of the students. It will use literature, and a cross-disciplinary approach, as appropriate, that is consistent with all other computer science courses. The course will avail students and faculty an opportunity to investigate computer science topics that are not part of the regular computer science curriculum. It fulfills an elective requirement for the Computer Science Major and Minor.

CSC 301: SYSTEMS ANALYSIS AND DESIGN

Credits 3

A course dealing with all aspects of system design and implementation. Problem definition, feasibility study, system design tools, system development control, and implementation and evaluation of systems will be covered.

CSC 303: OPERATING SYSTEMS

Credits 3

This course introduces operating system design emphasizing process management for multiuser and networked systems. Topics covered include: process scheduling, interprocess communication, race conditions and solutions, memory, device and file management.

CSC 305: DATA STRUCTURES

Credits 3

This course introduces complex data structures such as trees, lists, stacks, and matrices. It also covers the classification of an algorithm by computing its order. The algorithms that will be analyzed include various sorting and searching methods.

CSC 317: JAVA PROGRAMMING

Credits 3

Java is an object-oriented programming language with many interactive multimedia capabilities. This course covers the fundamentals of Java programming language, including how to write, debug, and execute Java programs. The course covers object-oriented programming techniques, as well as creating Java applets and applications.

CSC 321: DATABASE MANAGEMENT SYSTEMS

Credits 3

This course deals with both the operational and decision support environment of database systems. Topics include indexing, randomization, physical blocking, and relational and hierarchical structures. Previous experience at the level of CSC 175 or equivalent is recommended.

CSC 327: OPERATIONS RESEARCH

Credits 3

Concepts, methods, and introduction to the theory of optimization of linear systems. Topics to include simplex method, duality, sensitivity, formulation, and classic problems, e.g., maximal flow, travelling salesman, and assignment.

CSC 333: MACHINE LEARNING

Credits 3

This course studies the construction of computer algorithms that can learn from and make predictions on data sets. Methods for supervised learning (linear regression, logistic regression, regularization, support vector machines, decision trees, naïve Bayes, linear discriminant analysis) and unsupervised learning (k-means, principal component analysis, matrix factorization, singular value decomposition). Issues of feature selection, dimensionality reduction, bias-variance tradeoff, cross-validation.

CSC/CYB 230: NETWORKING AND DATA COMMUNICATIONS

Credits 3

This course expands upon the principles and current trends in computer networks as identified in Cybersecurity Fundamentals. Students will deepen their understanding of wide area networks (WANs), local area networks (LANs) and their architectures across which data travels and communicates. Subjects will include the open systems interconnection (OSI) model, transmissions control protocol / internet protocol (TCP/IP), open systems, topologies and internet connected devices. Through in-class projects, theoretical and practical approaches toward building and maintaining local area networks will be covered.

CSC/CYB 230: NETWORKING AND DATA COMMUNICATIONS

Credits 3

CSC/CYB 235: SECURING WIRED AND WIRELESS NETWORKS

Credits 3

This course provides students who have a basic understanding of computer networking and data communications with the methods and techniques used to secure networks. Students will be required to design and build a secure local area network, incorporating all elements of the seven layers of the OSI Model. Students will learn the capabilities, limitations and vulnerabilities of a cyber network that can be dynamic yet strong against aggressive hackers and virus outbreaks. Also the goal of this course is to provide students with both technical and theoretical approaches to the deployment, securing and defending of wireless networks. Topics will address network attacks, intrusion detection, malware, rogue wireless networks and wireless networking through the cloud. Students must already possess a basic knowledge of information security and networks. Team projects and presentations are required for completion.

CSC/CYB 235: SECURING WIRED AND WIRELESS NETWORKS

Credits 3

CYB 115: CYBERSECURITY FUNDAMENTALS

Credits 3

This course provides a bird’s eye view of the evolving cyberspace ecosystem, the interoperability of physical and social networks, and methods and techniques in securing that ecosystem. Students will explore the ethical, legal, and technical aspects of cybercrime and methods of prevention, detection, response, and recovery. The value of strong moral character, integrity, and trust as prized attributes of cybersecurity practitioners will be highlighted. Students will be introduced to essential cybersecurity topics including operating system models and mechanisms for mandatory and discretionary controls, data models, basic cryptography and its applications, security in computer networks and distributed systems, inspection and protection of information assets, detection of and reaction to threats to information assets, and examination of pre- and post-incident procedures, technical and managerial responses, an overview of the information security planning and staffing functions, data mining and data science, and policy and assurance issues. The advantages and inherent value of being prepared as a life-long learner with a strong liberal-arts background will be emphasized with the opportunity for students to complete a service-learning project tailored to their academic/career goals. No prior computer programming experience is required. Basic competency in computer operation is required.

CYB 265: OPERATING SYSTEMS ADMINISTRATION

Credits 3

Learn how best to protect computers, the data they store, process and transmit, and the users who use them, from a wide array of cybersecurity threats. This course will introduce students to operating systems administration within the context of cybersecurity. Students will learn how best to perform basic system administration operations with an emphasis on methods (e.g., managing applications, services, and network ports) to fortify the security of the computer’s operating system. The class will provide coverage of methods used in the Microsoft Windows® and Linux® operating systems.

CYB 299: SPECIAL TOPICS IN CYBERSECURITY

Credits 3

This course will explore a contemporary cybersecurity topic based on the interest of the professor and needs of the students. It will use literature, and a cross-disciplinary approach, as appropriate, that is consistent with all other cybersecurity courses. The course will avail students and faculty an opportunity to investigate cybersecurity topics that are not part of the regular cybersecurity curriculum. It fulfills an elective requirement for the Cybersecurity Minor.

CYB 304: CRYPTOGRAPHY

Credits 3

Cryptography is a key component in securing data while it is stored, processed, and transmitted. Cryptography components are found in computer applications and also utilized to secure network communications. This course will introduce students to the principles of cryptography, cryptographic number theory, including hash functions, symmetric and asymmetric cryptography, and their common applications in network security and corresponding susceptibility to attacks/failures. Students will learn how best to compare, select, and apply cryptographic approaches to fortify cybersecurity. Other topics include cryptographic algorithms and programming.

CYB 318: SOFTWARE AND APPLICATION SECURITY

Credits 3

Software security represents a key aspect in the field of cybersecurity. This course will ground students in the concepts of malware, malware analysis and preventive measures during software development that can mitigate malicious activity. Theoretical approaches to software security will be complemented by practical scenarios from which students can conduct future software design and investigations.

CYB 328: COMPUTER NETWORK FORENSICS AND DIGITAL INVESTIGATIONS

Credits 3

This course studies the technology and practice of investigating the abuse of computing systems and digital devices. As criminal and adversarial activity becomes faster and less visible over networks, students must understand how to search for, and extract information from, cyberspace. This course will provide unparalleled insight into digital forensics methods and laws, complemented with practical lab work. This course also introduces students to the theory and practice of network traffic analysis and intrusion detection. Students will learn “traceback” techniques and information retrieval methods to identify different attacks. Topics covered will include network forensics, intrusion detection and response, case studies, and issues of cyber law and ethics. Students must have basic knowledge of networking, and operating systems. Team projects and presentations are required for completion.

CYB 338: ETHICAL HACKING

Credits 3

This course will introduce students to ethical hacking and penetration testing methods, learning to think like a cyber-criminal and develop secure countermeasures. Students will learn the systematic approaches to planning, reconnaissance, vulnerability identification and exploitation methods used by hackers around the world to compromise the security of existing networks, systems, and applications. A variety of penetration-testing tools and techniques will be explored through hands-on activities. Identification of corresponding cybersecurity control recommendations will be highlighted.

CYB 401: PREPARING FOR CYBER DISASTERS

Credits 3

This course will provide students a full picture of securing a firm from a cyberattack. Topics will include preparatory measures that continuously investigate network integrity, data security, and backup archives. Students will also develop Cyber Disaster Response Plans that consider the legal, economic, and physical requirements needed to recover from a cyberattack.

CYB 438: INDEPENDENT CYBERSECURITY PROJECT OR INTERNSHIP

Credits 3

Students in the Cybersecurity program will have the option during one semester to conduct and present an independent cybersecurity project or intern part time with a cybersecurity employer in the business, government or nonprofit sectors. This course is designed to provide a culminating experience that avails students the opportunity to apply what they have learned to a contemporary cybersecurity project or internship experience that is framed by current cybersecurity industry trends and concerns. The course also helps students continue to improve skills critical to success in pursuit of their future academic and career aspirations.

MAT 111: INTRODUCTORY MATHEMATICS

Credits 3

An introductory course in basic algebra which covers the following topics: properties of real numbers, linear equations and inequalities, functions and graphs, polynomials, fractional algebra, radicals, and rational exponents. Not open to those who have completed any other mathematics course.

MAT 114: ELEMENTARY FUNCTIONS

Credits 3

A survey of those topics in algebra, trigonometry, and analytic geometry which provide the background for the study of calculus. Topics to be covered include exponential and logarithmic functions, complex numbers and polynomial functions, trigonometry, plane analytic geometry, and systems of linear equations and inequalities. Not open to those who have completed MAT 117 or 131.

MAT 117: CALCULUS I

Credits 3

An introductory course in differential calculus. Topics to be covered include limits and continuity, the derivative and applications, and an introduction to integration. Not open to those who complete MAT 131.

MAT 118: CALCULUS II

Credits 3

The continuation of MAT 117. Topics to be covered include the definite integral and applications, elementary techniques of integration. Not open to those who complete MAT 131 or MAT 132.

MAT 131H: ELEMENTARY CALCULUS I (HONORS)

Credits 3

A more rigorous introduction to calculus for entering students with good backgrounds in mathematics. Recommended for students considering a major in mathematics. Topics include the real numbers, functions, limits, the derivative and applications. Not open to those who complete MAT 117 or MAT 118.

MAT 132H: ELEMENTARY CALCULUS II (HONORS)

Credits 3

A more rigorous introduction to calculus for entering students with good backgrounds in mathematics. Recommended for students considering a major in mathematics. Topics include the integral and applications, and techniques of integration. Not open to those who complete MAT 117 or MAT 118.

MAT 150: NUMBERS AND OPERATIONS FOR EDUCATORS

Credits 3

In this course, students will investigate fundamental mathematics concepts associated with numbers, operations, and patterns. One of the major goals of the course is for students to develop deeper conceptual understandings of the mathematics concepts they will teach in the elementary and middle grades. Not only will students gain computational proficiency but also the ability to explain to students, in multiple ways, why mathematics concepts make sense. The course heavily emphasizes the use of open-ended problem-solving methods of teaching and learning to help students develop their own functional understanding of the major concepts. A significant focus of this course will be on problem solving, reasoning and proof, multiple representations, recognizing connections (across mathematics and other disciplines), and mathematical communication. The course is intended for students planning on pursuing a career in elementary or middle school education. As such, particular attention is given to understanding common misconceptions that children have when learning about specific mathematics concepts and considering the ramifications of these misconceptions for the development of effective classroom instruction. This course is a prerequisite for EDU 324: Mathematics Teaching in the Elementary Classroom.

MAT 151: ALGEBRA, GEOMETRY, AND DATA ANALYSIS FOR EDUCATORS

Credits 3

In this course, students will investigate fundamental mathematics concepts associated with algebra, geometry, and data analysis. One of the major goals of the course is for students to develop deeper conceptual understandings of the mathematics concepts they will teach in the elementary and middle grades. Not only will students gain computational proficiency but also the ability to explain to students, in multiple ways, why mathematics concepts make sense. The course heavily emphasizes the use of open-ended problem-solving methods of teaching and learning to help students develop their own functional understanding of the major concepts. A significant focus of this course will be on problem solving, reasoning and proof, multiple representations, recognizing connections (across content areas and disciplines), and mathematical communication. The course is intended for students planning on pursuing a career in elementary or middle school education. As such, particular attention is given to understanding common misconceptions that children have when learning about specific mathematics concepts and considering the ramifications of these misconceptions for the development of effective classroom instruction. Recommended for elementary education majors and middle/secondary mathematics education majors.

MAT 190: FACILITATING A MATH ACADEMY I

Credits 1

This course is part of a 2-course sequence intended to prepare students to be facilitators/leaders of the Assumption Institute of Mathematics (Camp AIM) in Summer 2025. Students will learn about basic teaching best practices to engage and motivate high school students, receive an introduction to examples of mathematics activities that could be used with high school students during Camp AIM, and develop ideas about the content of the Camp AIM program. This course will meet for one hour per week. The companion spring course is EDU 190 Facilitating a Math Academy II.

MAT 202: DISCRETE STRUCTURES

Credits 3

This course is an introduction to mathematical logic and discrete systems. Topics include Boolean algebra, mathematical proof, sets, relations, functions, induction, combinatorics, graph theory, and applications.

MAT 203: LINEAR ALGEBRA

Credits 3

Linear systems of equations, matrix algebra, determinants, vector spaces, linear transformations, matrix representations of linear transformations, and applications.

MAT 204: NUMBER THEORY

Credits 3

Divisibility theory, prime factorization, congruences, Fermat’s theorems, the phi-function, Euler’s Theorem, and applications.

MAT 207: ACTUARIAL MATHEMATICS

Credits 3

Mathematical theory and practical application of compound interest, including the measurement of interest, annuity calculations, loan repayment, and security valuation. Stress laid on theoretical foundations, derivations, and proofs. Introduction to financial simulation.

MAT 208: PROBABILITY THEORY

Credits 3

Combinatorial problems, conditional probability, dependence and independence, probability measures, distributions, and stochastic processes.

MAT 231: CALCULUS III

Credits 3

A second-year course in calculus, designed to follow either MAT 118 or MAT 132. Topics to be covered include improper integrals, sequences and series, parametric curves, polar coordinates, and vector geometry.

MAT 232: MULTIVARIABLE CALCULUS

Credits 3

A course in the calculus of functions of several variables. Topics to be covered include multivariable functions, partial derivatives, multiple integrals and the theorems of Green, Gauss, and Stokes.

MAT 299: SPECIAL TOPICS IN MATHEMATICS

Credits 3

This course will explore a mathematics topic based on the interest of the professor and needs of the students. It will use literature, and a cross-disciplinary approach, as appropriate, that is consistent with all other mathematics courses. The course will avail students and faculty an opportunity to investigate mathematical topics that are not part of the regular mathematics curriculum. It fulfills an elective requirement for the Mathematics Major and Minor.