A. All of the following
Note: Students take either M148 Calculus I with Precalculus and M149 Calculus I with Precalculus, or M151 Calculus I.
M148 Calculus I with Precalculus (part 1) (4 cr.)
This course, followed by M149, provides a two-semester sequence that covers the material of M151 along with built-in coverage of precalculus topics. Topics in M148 include: solving equations, functions, classes of functions (polynomial, rational, algebraic, exponential, logarithmic), right triangle trigonometry, angle measure, limits and continuity, derivatives, rules for derivatives. Credit is not granted for this course and M151 or courses equivalent to college algebra and college trigonometry.
M149 Calculus I with Precalculus (part 2) (4 cr.)
This course completes the two-semester sequence that begins with M148, and together with M148 provides a two-semester sequence that covers the material of M151 along with built-in coverage of precalculus topics. Topics in M149 include: trigonometric and inverse trigonometric functions, rules for derivatives, applications of derivatives, and definite and indefinite integrals. Credit is not granted for this course and M151.
M151 Calculus I (4 cr.)
This course provides an introduction to the differential and integral calculus. Topics include: the concepts of function, limit, continuity, derivative, definite and indefinite integrals, and an introduction to transcendental functions. Credit is not granted for this course and M148 and M149.
M152 Calculus II (4 cr.)
This course continues the development of calculus. Topics include: applications of the definite integral, techniques of integration, improper integrals, introduction to differential equations, numerical methods for integration and approximation, curves in the plane given parametrically, polar coordinates, and vectors in 2-space and 3-space.
M251 Calculus III (4 cr.)
This course continues the development of calculus. Topics include: sequences and series, and differentiation and integration of vector-valued functions and functions of several variables.
B. All of the following:
M252 Linear Algebra (4 cr.)
This course provides an introduction to techniques and applications of linear algebra. Topics include: systems of linear equations, matrices, determinants, Euclidean n-space, real vector spaces, basis and dimension, linear transformations, inner products, and eigenvalues and eigenvectors.
M301 Foundations of Advanced Mathematics (2 cr.)
This course looks at topics central to further study in mathematics. Topics include symbolic logic, especially as it applies to mathematical proof; methods of mathematical proof such as direct proof, indirect proof, proof by induction; use and meaning of mathematical quantifiers and predicates; sets; relations; equivalence relations and partitions; order relations; functions and their properties; and complex numbers. A junior assessment test is administered as part of this course.
M332 Probability (2 cr.)
This calculus-based course is designed to provide mathematics majors and minors with an introduction to the mathematical underpinnings of statistics. Topics include: probability axioms, probability, Bayes' Theorem, random variables, discrete and continuous probability distributions, and expected value.
M401 Abstract Algebra (3 cr.)
This course provides an introduction to algebraic structures. Topics include: groups, subgroups, quotient groups, group homomorphisms, rings, ideals, and fields.
M411 Introduction to Analysis (3 cr.)
This course provides a rigorous treatment of topics in calculus. Topics include: sequences, functions, limits, continuity, derivatives, and integration.
M491 Senior Seminar (2 cr.)
This course consists of student presentations from mathematics, mathematical modeling, mathematics education, or statistics. Each student chooses a topic in consultation with the instructor, does appropriate background reading, and prepares an oral presentation and written paper on the topic. A senior assessment test is administered as part of this course.
ST232 Introduction to Statistics (2 cr.)
This course is designed to provide the basic ideas and techniques of statistics. Topics include: descriptive and inferential statistics, an intuitive introduction to probability, estimation, hypothesis testing, chi-square tests, regression and correlation. This course makes significant use of appropriate technology. Topics in this course are treated at a higher mathematical level than they are treated in ST132 Reasoning with Statistics.
Credit is not granted for this course and any of the following: BU215 Business Statistics, B392 Biostatistics, or ST132 Reasoning with Statistics.
C. Both of the following:
M321 Modern Geometry (3 cr.)
This course is required for the Mathematics Education major. The course is designed to be an introduction to the foundations of geometry. Topics include: Euclidean geometry, non-Euclidean geometry, projective geometry, and geometric transformations.
M361 Operations Research (3 cr.)
This course is required for the Mathematics Education major, providing an introduction to techniques and applications of operations research. Topics include: linear programming, game theory, queuing theory, Markovian decision processes, and decision theory.
D. Two of the following courses
Two of the following courses; or one of the following courses and one course in another field using mathematics with the approval of the major advisor and the department chair.
M310 Combinatorics and Graph Theory (3 cr.)
This course provides an introduction to combinatorial and graph theoretical techniques in mathematics. It is also designed for students in computer science. Topics include: sets, functions, combinatorial techniques, graph theory, searching algorithms, and trees.
M315 Number Theory (3 cr.)
This course provides an introduction to elementary number theory. Topics include: divisibility, prime and composite numbers, congruences, arithmetical functions, primality testing, factorization techniques, and applications to cryptography.
M341 Differential Equations with Applications (3 cr.)
This course provides an introduction to the theory, methods, and applications of ordinary differential equations. Topics include: first order differential equations, linear differential equations with constant coefficients, and systems of differential equations.
M342 Numerical Analysis (3 cr.)
This course provides an introduction to the theory and methods of numerical analysis. Topics include: numerical methods for solving linear and nonlinear equations, polynomial approximation of functions, numerical integration and differentiation, numerical approximation to solutions of differential equations, direct and iterative methods for solving systems of equations.
M344 Applied Mathematics (3 cr.)
This course serves physics majors as well as those mathematics majors whose area of interest is analysis. Topics include: Fourier series, the complex numbers, analytic functions, and derivatives and integrals of complex functions. Other topics may include Laurent series and residues, partial differential equations and boundary value problems.
M348 Complex Analysis (3 cr.)
This course provides an introduction to the theory of functions of one complex variable. Topics include: the complex numbers, the complex derivative, analytic functions, power series, complex integration, Cauchy's Theorem and Cauchy's Integral Formula, Laurent series, and residues and poles.
M356 Introduction to Scientific Computing (3 cr.)
This course is designed to provide undergraduates students with the basic computational tools and techniques needed for their study in science and mathematics. Students learn by doing projects that solve problems in physical sciences and mathematics using symbolic and compiled languages with visualization. By use of the Sage problem-solving environment and the Python programming language, the students learn programming and numerical analysis in parallel with scientific problem solving.
M380-389 Special Topics (3 cr.)
Special topics in mathematics may be offered depending on student interest.
M496/497 Mathematics Internship (1–17 cr.)
This opportunity provides the student with experience in mathematical research or applications. The internship must be approved by the department chair and, depending on the nature of the internship, may be counted towards the major. Students generally are expected to give a presentation following the internship.
ST350-359 Special Topics (3 cr.)
Selected topics in statistics may be offered depending on student interest.
ST371 Applied Regression Analysis (3 cr.)
This course provides students with an introduction to linear and non-linear models in statistics. Topics include: linear regression, multiple regression, one-, two-, and higher-way analysis of variance, and popular experimental designs. Real-world problems are analyzed using appropriate technology.
ST373 Design of Experiments (3 cr.)
This course provides an introduction to the principles of the design of experiments from a statistical perspective. Topics include: Analysis of variance, covariance, randomization, completely randomized, randomized block, Latin-square, factorial, response surface methods and other designs.
ST431 Mathematical Statistics (3 cr.)
This course provides a mathematical treatment of probability and statistics. Topics include: several descriptions of the concept of probability, univariate and bivariate probability distributions, joint and marginal probability distributions, covariance, data analysis, and sampling distributions.
ST496/497 Statistics Internship (1–17 cr.)
This opportunity provides the student with experience and training in statistical techniques. The internship must be approved by the department chair and, depending on the nature of the internship, may be counted towards the major. Students usually are expected to give a presentation following the experience.
E. Either CS106 or CS110
CS106 Introduction to Programming for Sciences (3 cr.)
This course teaches introductory programming within a problem-solving framework applicable to the sciences. The course emphasizes technical programming, introductory data storage techniques, and the processing of scientific data. There is an emphasis on designing and writing correct code using an easy to learn scientific programming language such as Python. Advanced excel spreadsheet concepts will be taught and utilized during the programming process. Credit is not granted for this course and CS110.
CS110 Computer Science I: Introduction to Programming (3 cr.)
This course introduces students to the practice of software development. Students learn the fundamentals of programming, algorithm development, and basic design principles.
F. Required education course work