59 courses with the subject MA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
MA 026Math Readiness & Success
This course does not carry academic credit and has no impact on a student's grade point average (GPA). Pre-req: No ALEKS PPL score above 45. Students with credit in any of the following courses cannot take MA 026: MA 105/MA 105L/MA 105P, MA 107/MA 107L, MA 131/MA 131L, or MA 139/ MA 139L. This course is not open to exchange students. This online course supports students as they continue building and strengthening the algebraic and problem solving skills needed for success in college level mathematics. Through targeted practice and guided support, students develop fluency in core quantitative concepts, and deepen their mathematical reasoning. Successful completion of this course satisfies the prerequisite for required introductory math courses. n Typically Offered: Fall and Spring
or MA 105L Mathematical Foundations for Business with Lab or MA 105P Mathematical Foundations for Business with Prep or MA 107 Applied Calculus for Business or MA 107L Applied Calculus for Business with Lab or MA 131 Calculus I or MA 131L Calculus I with Lab Total Credits 15 Context and Perspectives (18 Credits) Course Title Credits Students must take six courses, one in each category of Context and Perspectives: 3 Culture, Change, and Behavior (p. 10) 3 Globalization (p. 11) Institutions and Power (p. 12) 3 Race, Gender, and Inequality (p. 13) 3 Scientific Inquiry (p. 14) 3 Values, Ethics, and Society (p. 14) 3 Total Credits 18 Business Dynamics/Business Administration Minor (18
MA 105LMathematical Foundations for Business with Lab3
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement This course presents concepts of three mathematical modeling topics (linear programming, mathematics of finance and probability) that are of particular relevance to business applications. Linear Programming can be helpful in allocating limited resources among various activities. Mathematics of Finance introduces the mathematical methods used in evaluating financial instruments such as loans and bonds. Probability aids in understanding the impact of uncertainty of future events on decision-making. Effective communication of results will be emphasized. Typically Offered: Fall and Spring
MA 105PMathematical Foundations for Business with Prep3
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement This course reinforces foundational concepts from college algebra and studies their application to three core areas of mathematical modeling- linear programming, mathematics of finance, and probability—each selected for their relevance to real-world business decision-making. Students will develop algebraic fluency while learning to: • Apply linear programming techniques to optimize resource allocation across competing activities. • Use the mathematics of finance to evaluate financial instruments such as loans, annuities, and bonds. • Analyze probability models to assess risk and uncertainty in future events and their impact on strategic choices. Emphasis will be placed on interpreting and communicating mathematical results effectively, both in written and verbal formats. Through problem-solving, and collaborative work, students will gain quantitative reasoning skills applicable to business, economics, and everyday decision-making. Typically Offered: Fall and Spring
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement The course presents concepts of differential and integral calculus, introduces functions as simple mathematical models, and develops students’ quantitative reasoning skills. Specific emphasis will be placed on the understanding of as well as the use of tools relevant to solving problems in business and economics. Topics include derivatives, indefinite and definite integrals and applications to marginal profit/ revenue/cost, optimization, continuous income streams and consumer’s/ producer’s surplus. Typically Offered: Fall and Spring
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement The course presents concepts of differential and integral calculus, introduces functions as simple mathematical models, and develops students’ quantitative reasoning skills. Specific emphasis will be placed on the understanding of as well as the use of tools relevant to solving problems in business and economics. Topics include derivatives, indefinite and definite integrals and applications to marginal profit/ revenue/cost, optimization, continuous income streams and consumer’s/ producer’s surplus. Typically Offered: Fall and Spring
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement This course presents a thorough treatment of differential calculus that assumes a solid foundation in algebra and trigonometry. Topics include limits and continuity; the differentiation of single-variable functions; implicit and logarithmic differentiation; curve sketching; optimization; and applications to business, economics, and the social and natural sciences. Typically Offered: Fall and Spring
Pre-Req: Students starting Fall 2025 or later must demonstrate competency through the ALEKS PPL Placement Assessment. https://www.bentley.edu/ offices/student-success/mathplacement This course presents a thorough treatment of differential calculus that assumes a solid foundation in algebra and trigonometry. Topics include limits and continuity; the differentiation of single-variable functions; implicit and logarithmic differentiation; curve sketching; optimization; and applications to business, economics, and the social and natural sciences. Typically Offered: Fall and Spring
Pre-Req: MA 131 or MA 131L This course is a continuation of MA 131. It presents a thorough treatment of integral calculus. Topics include integrating single-variable functions, including indefinite, definite and improper integrals by substitution, parts and partial fraction expansion; an introduction to ordinary differential equations; and applications to probability, business, economics, and the social and natural sciences. Typically Offered: Fall
Pre-Req: MA 107, MA 107L, MA 131, or MA 131L This course introduces basic concepts of dynamical systems through lectures, slides, films and computer experimentation. Students predict system behavior based on mathematical calculations and on observation of computer results (no computer programming experience is necessary). Topics include iteration of functions, Julia sets, Mandelbrot sets, chaos and fractals. Typically Offered: Once a year
Pre-Req: ST 113 Context and Perspectives: Scientific Inquiry Statisticians have assumed larger and more important roles in the modern world as corporate problems become more complex. Feedback from statisticians is used by managers at all levels, especially as data sets become larger. In MA214, you will be asked to conduct hypothesis tests on multiple populations, learn to analyze variance, see applications of multiple regression and analyze contingency tables. The statistical functions in EXCEL will be complemented by a higher-level statistical package. The course will focus on applications drawn from the primary business disciplines. Typically Offered: Fall and Spring
Pre-req: MA 214 Sport Analytics introduces students to the use of analytical methods to better understand athletic competitions and enhance individual and team performance. The course covers both statistical topics—such as expectations, probability, and risk/reward analysis—and deterministic approaches including optimization, ranking, and validation. Students will work with a variety of software tools to explore how mathematical thinking can inform athletes, coaches, and fans, offering deeper insights into the dynamics of sports. Typically Offered: Once a year
Pre-Req: Three credits of math This course is an introduction to linear optimization models as they apply to problems in business and economics. The potential and limitations of various models are discussed. Emphasis is placed on developing models from written descriptions and interpreting model solutions, typically computer-generated. Specific topics include linear and integer programming models. Typically Offered: Every two or more years
MA 225Probability Models for Business Decision-Making3
Pre-Req: ST 113 This course is an introduction to probabilistic models as they apply to management, economic and business administration problems. The potential and limitations of various models are discussed. Emphasis is placed on developing models from written descriptions and interpreting model solutions, typically computer-generated. Specific topics include an introduction to basic probability, decision analysis, queuing models and simulation. Typically Offered: Every two or more years 2026-2027-Undergraduate 247
Pre-Req: MA 139 or MA 139L This course includes such topics as sequences and series (including geometric and Taylor series); multivariable differential and integral calculus; vector calculus; and applications to business, economics, and the social and natural sciences. Typically Offered: Fall and Spring
Pre-Req: MA 139 or MA 139L This is an introductory course in ordinary differential equations with application to the social and natural sciences. First-order differential equations, second-order linear equations with constant coefficients and first-order linear systems are examined. The emphasis is on formulation of equations (modeling), analytical and graphical solution techniques and interpretation of solutions (prediction). Solution techniques include the methods of integrating factors, undetermined coefficients and variation of parameters. Linear first-order and second-order difference equations with applications are also introduced. Computer experiments are carried out in MATLAB and PHASER. Typically Offered: Once a year
Pre-req: MA 139 This course covers an introduction to proof methods used in advanced mathematics as well as the theory of the analysis of real-valued functions of a single variable. Tools from mathematical analysis are used in fields such as finance, economics, actuarial science, and data science, and is a building block mathematical thinking. Coverage will include logic, sets, cardinality, induction, completeness, point set topology, continuity, convergence of sequences, and derivatives. Students will not only learn how to communicate and discuss mathematics accurately and effectively but will also develop their critical thinking skills and leave the class with a greater understanding of how to think about mathematics more abstractly. Typically Offered: Spring
Pre-Req: Three credits of math This course relates to problems of a probabilistic nature in business, economics, management science and the social sciences. It includes such topics as set notation, permutations, combinations, mutually exclusive and independent events, conditional probability, Bayes' Theorem, expectation and dispersion, Markov chains and decision- making.This course introduces the common discrete distributions: binomial, hypergeometric, geometric, negative binomial and Poisson. Simulation may be used where appropriate. Typically Offered: Fall and Spring
Pre-Req: MA 252 Context and Perspectives: Scientific Inquiry The course addresses the design and analysis of experiments, with a focus on management applications. The differences, advantages and disadvantages of various designs are discussed with a special emphasis on factorial and fractional factorial designs. These popular designs allow for two or more factors to be systematically and simultaneously varied while the experimenter tries to determine not only the (main) effect of each factor, but also how the level of one factor influences the impact of another factor (aka interaction). Students will extend the long history of successes of the (fractional) factorial design into the field of management inquiry. Specific applications will stress cost savings and policy making; multiple examples will be drawn from the marketing disciplines. Typically Offered: Fall and Spring
Pre-Req: ST 113 and MA 139 This course focuses on concepts and techniques of continuous probability and their applications to risk management in insurance and finance. Among other topics, the most commonly used single- and multi- variable continuous probability distributions are addressed. Concepts are illustrated with a large number of applied risk management problems. Typically Offered: Fall
Pre-Req: Three credits of Math In contrast to the continuous real number line from calculus, "discrete" mathematical structures are made up of distinct, separate parts. The instructor chooses a few topics to cover from the many available discrete mathematics topics, including mathematical language and syntax, proofs and logic, circuits, cryptography, graphs (i.e., relationships among people, agencies, machines, and more.), number theory, combinations and permutations, and similar topics. The relationship of mathematics to computer science features prominently. Typically Offered: Every two or more years
MA 280Selected Topics in the Mathematical Sciences3
This course examines a particular area of mathematics or its applications. It may include such topics as the use of mathematical models in environmental science, the history of mathematics, elementary measure theory or financial mathematics. The topic will be announced prior to registration. Typically Offered: As needed
Experimental courses explore curriculum development, with specific content intended for evolution into a permanent course. Students may repeat experimental courses with a different topic for credit. Typically Offered: As needed
Experimental courses explore curriculum development, with specific content intended for evolution into a permanent course. Students may repeat experimental courses with a different topic for credit. Typically Offered: As needed
Pre-req: MA 214 Students who have completed MA 602 are not eligible for this course This course provides a comprehensive introduction to the major components of the health sector and the quantitative data analysis tools used to study health problems. Students will explore the role of statistics and mathematics in addressing issues such as health outcomes, health care costs, clinical decision-making, and management optimization, such as resource allocation. The course introduces key quantitative data analysis methods, including statistical inference, simple and multiple regression, mathematical modeling, and optimization. It then demonstrates their use through applications in health outcome analysis, clinical studies, health services, health insurance, and health cost for various health decision-making scenarios. Typically Offered: Fall
Pre-Req: Three credits of Math This course introduces mathematics for analyzing and describing images and scenes. Manipulations of two- and three-dimensional figures and spaces are analyzed using geometry, vectors, matrices and polynomials. A significant aspect of the course involves using these mathematical methods to generate images and animations that are both attractive and informative. Typically Offered: Other
Pre-Req: Six credits of math or [(MA 107 or MA 107L or MA 131 or MA 131L) and ST 113] Game theory is the study of strategic behavior of rational actors who are aware of the interdependence of their actions. Course topics include the extensive form tree representation and the key concepts of strategy space and strategy profile. The normal form game representation is developed and illustrated with classical games such as the Prisoner's dilemma and Hawk-Dove. The discrete probability model is developed and applied to the concepts of player beliefs and mixed strategies. Solution concepts for games such as dominance and iterated dominance, best response curves, Nash equilibrium and security strategies are developed and compared. Additional topics may also be included, such as evolutionary games and fair division strategies. Typically Offered: Every two or more years
Pre-Req: MA 214 While Microsoft Excel is not an ideal analytics tool, it is ubiquitous in business contexts, making it often the best platform to share work with colleagues and clients. This is particularly true when creating an automated analysis and sharing it with nontechnical users, who need a familiar interface. Consequently, we cover in this course ways to create and automate various analytical techniques in the programming language VBA (Visual BASIC for Applications) that is built into Microsoft Excel. We will focus on using it for mathematical modeling, automating analyses, and creating user interfaces inside of Excel for sharing an automated analysis tool with a nontechnical user. Typically Offered: Once a year 2026-2027-Undergraduate 249
Pre-Req: MA 139 and ST 113 This course provides an introduction to the basic mathematical concepts underlying the famous Black-Scholes-Merton option pricing formula and the associated financial market model, including model limitations and alternatives. Selected topics from ordinary differential equations, probability theory and statistics are used to develop and analyze the economic concepts. Hedging strategies and portfolio sensitivity parameters associated with options are also developed and discussed. Typically Offered: Spring
MA 343The Mathematics of Discrete Options Pricing3
Pre-Req: ST 113 This course is devoted to basic principles and techniques of no-arbitrage discrete derivative pricing. Using elementary probability and linear algebra, the binomial option pricing model is developed. No-arbitrage option pricing and hedging are addressed using binomial trees. Real- market data is used to explore the computational aspects of options pricing. The course should be of interest to strong math students who would like to see how fundamental mathematics is applied to a significant area of finance and to strong finance and economics students who would like to better understand the concepts behind the standard options pricing models. Typically Offered: Fall
Total Credits 12 CS 370 is an approved substitution for CS 350 for Computer Information Systems majors only. MA 347 or MA 250 are approved substitutions for MA 214 for Actuarial Science and Mathematical Sciences majors only. 26-2027-Undergraduate 99
Pre-Req: MA 252 Context and Perspectives: Scientific Inquiry This course will introduce participants to the most popular supervised and unsupervised statistical machine learning techniques, with an emphasis on getting a general understanding of how the method works, how to perform the analysis using suitable available software, and how to interpret the results in a business context. Topics will include linear regression models, logistic regression models, association rules analysis (also known as market basket analysis), cluster analysis, k-nearest neighbors, decision tree analysis, and Naïve Bayes. Additional techniques may be introduced if time allows. Typically Offered: Fall and Spring
Pre-Req: MA 139 or MA 139L The theory of interest addresses the critical financial question of determining the value of a stream of cash flows. This is a problem-solving intensive course aimed at preparing the highly motivated student for the Society of Actuaries Exam FM. Emphasis is placed on learning efficient and effective techniques for solving interest theory problems. Typically Offered: Spring
MA 374Fundamentals of Short-Term Actuarial Mathematics3
Pre-Req: MA 263 This course introduces fundamental topics of actuarial mathematics for short-term coverages that are applicable for health, life, and property/ casualty insurance. We will focus on modeling techniques, such as frequency, severity, coverage modifications, and aggregate models, as well as the principles of ratemaking and reserving. This course will cover most of the short-term modeling topics on the Society of Actuaries Exam FAM and the Casualty Actuarial Society Exam 5. Typically Offered: Every two or more years
MA 375Fundamentals of Long-Term Actuarial Mathematics3
Pre-Req: MA 263 and MA 357 This course introduces fundamental topics of actuarial mathematics for long-term coverages. We will examine survival models, contingent payment models (present value random variables, premium, and policy valuation) and their applications to insurance and other financial risks. This course will cover most of the long-term modeling topics on the Society of Actuaries Exam FAM. Typically Offered: Every two or more years
Pre-req: MA 233 and MA 375 This course further develops knowledge and mastery of fundamental actuarial mathematics, focused on long-term insurance, health, and annuity contracts. We begin with survival models for multiple state contingent cash flows and use them to calculate premiums and policy values for long-term coverages. Then we consider joint life insurance and annuity contracts and their profit metrics. Finally, we explore how retirement benefits are accrued, valued, and funded. This course is designed to help a motivated student prepare for the Society of Actuaries (SOA) ALTAM examination. Typically Offered: Every two or more years
MA 398Experimental Course in Actuarial Ratemaking and Reserving3
Pre-Req: MA 214 and MA 263 This course introduces basic ratemaking and reserving practices and techniques. These techniques are fundamental to a well-rounded actuarial education and should be of interest to all actuarial students. Both ratemaking and reserving are key actuarial responsibilities and this course will offer a hands-on/project based approach to learning the techniques and understanding the impact on insurer profitability. The concepts and skills we develop are particularly relevant to short term coverages as is typically found in health and property and casualty contracts. We will analyze data, build models in Excel, update them as new data becomes available, and make recommendations to management. Typically Offered: Once a year
Experimental courses explore curriculum development, with specific content intended for evolution into a permanent course. Topics may be offered twice before it becomes a permanent course. Students may repeat experimental courses with a different topic for credit. Typically Offered: As needed
Pre-Req: Three credits of math This course permits small-group study of selected topics by advanced students. (May be repeated for credit.) Typically Offered: As needed
An internship provides students with an opportunity to gain on-the- job experience and apply principles and issues raised in the academic discipline to a work environment. The student is required to attend pre- internship workshops sponsored by the Center for Career Services, meet regularly with a faculty advisor, and develop a final paper or special project. Typically Offered: As needed
Pre-req: ST 625Not open to students who have completed MA 302 This course provides a comprehensive introduction to the major components of the health sector and the quantitative data analysis tools used to study health problems. Students will explore the role of statistics and mathematics in addressing issues such as health outcomes, health care costs, clinical decision‑making, and management optimization, such as resource allocation.The course introduces key quantitative data analysis methods, including statistical inference, simple and multiple regression, mathematical modeling, and optimization. It then demonstrates their use through applications in health outcome analysis, clinical studies, health services, health insurance, and health cost for various health decision‑making scenarios. Typically Offered: Fall
MA 610Optimization and Simulation for Business Decisions3
Pre-Req: GR 521, GR 521D, or GR 521P Optimization and simulation methods are being used as effective tools in many environments that involve decision making. This course covers classical and modern optimization techniques used today in a business environment. Specifically, the focus will be on linear and nonlinear programming techniques with applications, as well as elective topics selected from game theory, agent-based modeling, and modern simulation and optimization techniques. Examples of application areas of optimization include portfolio selection in finance, airline crew scheduling in the transportation industry, resource allocation in healthcare industry, and minimizing the cost of an advertising campaign in marketing. e Typically Offered: Fall and Spring
Pre-Req: ST 625. Not open to students who have completed EC 621 This course examines methods for analyzing time series. In many data modeling situations, observations are collected at different points in time and are correlated. Such time series data cannot typically be modeled using traditional regression analysis methods. This course provides a survey of various time series modeling approaches, including regression, smoothing and decomposition models, Box-Jenkins analysis and its extensions, and other modeling techniques commonly used, such as quantile estimation and value at risk. It makes use of statistical packages such as SAS, JMP, R andor SPSS. Typically Offered: Fall and Spring
A Directed Study is designed for highly qualified students who, under the direction of a member of the sponsoring academic department, engage in an agreed-upon in-depth independent examination, investigation or analysis of a specialized topic. Typically Offered: As needed
Pre- or Co-Req: GR 521, GR 521D, or GR 521P Working with and finding value in data has become essential to many enterprises, and individuals with the skills to do so are in great demand in industry. The required skill set includes the technical programming skills to access, process and analyze a large variety of data sets, including very large (big data) data sets, and the ability to interpret and communicate these results to others. Anyone with these abilities will provide benefit to their organization regardless of their position. This course presents the essentials of this skill set. Typically Offered: Fall and Spring
Pre-Req: ST 625 This class is planned for those interested in the design, conduct, and analysis of experiments, with an emphasis on business applications. The course will examine how to design experiments, carry them out, and analyze the data they yield. Various designs are discussed and their respective differences, advantages, and disadvantages are noted. In particular, factorial and fractional-factorial designs are discussed in great detail. It has been found to allow cost savings, while revealing the essential nature of the impact of the factors studied, in a manner readily understood by those conducting the experiment as well as those to whom the results will be reported. Typically Offered: Spring
Pre or Co-Req: ST 635 Pre-Req: MA 705 or CS 602 or instructor permission This course provides students with knowledge of the fundamental concepts in machine learning and several state-of-the-art developments with an emphasis on real-world application. Topics include the machine learning landscape; model selection, feature engineering, parameter tuning, and model validation; popular supervised learning methods; unsupervised learning including clustering, principal component analysis, and manifold learning; text analysis and topic modeling; neural networks and deep learning. Students will gain hands-on experience implementing a wide variety of methods using the computer programming language of Python. Typically Offered: Every two or more years
Pre-Req: ST 635 This course introduces participants to the most recent data-mining techniques, with an emphasis on: (1) getting a general understanding of how the method works, (2) understanding how to perform the analysis using suitable available software, (3) understanding how to interpret the results in a business research context, and (4) developing the capacity to critically read published research articles which make use of the technique. Contents may vary according to the interest of participants. Topics will include decision trees, an introduction to neural nets and to self-organizing (Kohonen) maps, multiple adaptive regression splines (MARS), genetic algorithms, association (also known as market basket) analysis, web mining and text mining, and social networks. Typically Offered: Fall and Spring
This course offers an in-depth exploration of an advanced or emerging methodological topic in statistics, mathematics, or data science. Topics vary by semester and may include specialized modeling techniques, theoretical frameworks, or computational approaches beyond the scope of standard coursework. The course may be conducted in a seminar format, with students actively engaged in developing and presenting course materials. Typically Offered: As needed
ST 635, CS 605, MA 705 This course is a project course for students in the MS Business Analytics program. Students will work on either research projects or real-world problems, with faculty and/or a field supervisor advising. Students are provided with an opportunity to apply advanced skills to solve practical projects and they will learn how to tackle a business analytics problem from problem translation, data wrangling, statistical model building, translation of results, and achievable recommendation with statistical thinking and innovation. Typically Offered: Fall
Prereq: ST 635, CS 605 and MA 611 Experimental courses explore curriculum development, with specific content intended for evolution into a permanent course. Topics may be offered twice before becoming a permanent course. Students may repeat experimental courses with a different topic for credit. Typically Offered: As needed Professional MBA Essentials (PME)
