Overview | Requirements | Courses | Faculty


Mathematics, encompassing several of the original liberal arts, is valued for its exquisite intellectual beauty and its timeless exploration of all things spatial, quantitative and patterned through the lens of rigorous abstraction. As a vibrant modern science, it possesses an unparalleled analytical power for describing, detailing and deriving insight into numerous physical, biological, technological, economic and societal aspects of the world we all live in. The Mathematics department is committed to engaging a diverse range of students in the active study and creative application of the principles, ideas, and methods that characterize mathematics and the mathematical sciences, and offering preparation toward a wide variety of careers and educational pursuits.

Upon graduation, some mathematics majors go on to graduate or professional school while others begin careers in teaching, business, industry, or government. The major can be structured to provide a solid foundation in the mathematical sciences-pure and applied mathematics, statistics, and operations research-and fields close to mathematics like computer science, actuarial science, and engineering. A major or minor in mathematics can also provide an excellent technical and theoretical complement to a major or minor in other fields.

Computer Science is a rapidly developing field, rooted in mathematics but playing an increasingly important role in a wide range of human endeavors. Undergraduate study of computer science can lead to a variety of opportunities for employment or graduate work, as well as giving one insight into the greatest revolution in information technology since the invention of printing.

Please consult the Mathematics department's home page for more detailed and regularly updated information on the program.



MAJOR: The minimum requirements for the major outlined below permit students great flexibility in designing a course of study to meet their own intellectual and career goals.

Fundamental courses: Calculus 1, 2, Mathematics 210, Mathematics 212, and Mathematics 214. 

Any student who places out of a Calculus 1 or 2 class satisfies the corresponding requirement for the Math Major.

Advanced courses: Students must have 24 units of Mathematics courses numbered 310 or above (excluding Mathematics 400) in which their grade point average is equal to or greater than 2.0.

Colloquium requirement: Mathematics 300 and 400.

Breadth requirement: Mathematics 150; or any 4 units of Computer Science courses; or a 2-unit Computer Science course coupled with Mathematics 160.

The Mathematics department has prepared guidelines for majors considering future study or careers in pure and applied mathematics, education, actuarial science, and computer science. These guidelines are available on our website.

WRITING REQUIREMENT: Students majoring in Mathematics should familiarize themselves with this requirement at the time of declaring the major. The Third-Year Writing Requirement is addressed in Mathematics 300. Students not taking Mathematics 300 (e.g., study abroad students) may petition to satisfy the writing requirement at a different time.

COMPREHENSIVE EXAMINATION: This examination has two parts. The first part measures competence in the fundamental courses and is handled during Mathematics 300: Junior Colloquium. The second part consists of an independent project culminating in a written report and public presentation during the senior year, and is handled through Mathematics 400: Senior Colloquium. Further information is available from the department.

MINOR: At least 12 units from Mathematics 150, 210, 212, and 214. In addition, at least one 300-level 4-unit course is required. Students must take at least 20 units or the equivalent of five semester-courses in Mathematics at Occidental or through college transfer (not AP) credit to earn the minor in Mathematics. The grade point average for all Mathematics courses taken at Occidental and through college transfer must be at least 2.0.

HONORS: Students who wish to be considered for honors in mathematics should complete at least the five fundamental courses in their first two years with a grade point average greater than 3.0. Honors students must complete three approved upper division courses beyond those required for the major. These courses should be chosen to prepare the student for the senior honors project. Honors students enroll in Mathematics 499 to prepare this project, which is substituted for Mathematics 400 in satisfying the major requirements. Consult the Mathematics Department and the Honors Program for additional details.

CALCULUS PLACEMENT: Placement in calculus courses (Mathematics 108, 110, 114, or 128) is determined in part by the Calculus Placement Exam, administered online prior to the beginning of Fall Semester. Students achieving a score of 3, 4, or 5 on the College Board Advanced Placement Examination in Calculus (AB or BC) are exempt from the Calculus Placement Examination.

Students will be placed into Mathematics 108, 110, 114, or 128 based on previous mathematical experience, advising, and the results of the Calculus Placement Exam. Students with qualifying scores on the Advanced Placement Examination in Calculus are most often placed in calculus courses as follows:

Calculus AP Exam ScoreWhich Math course to take
BC 4 or 5150, 210, 212, or 214.
BC 3 (AB sub-score of 4 or 5)128 (possibly 120 after consultation with Math Dept)
BC 3 (AB sub-score of 1, 2 or 3)108, 114, or 120: attend Math Advising Session
BC 1 or 2Take Calculus Placement Exam
AB 4 or 5128 (possibly 120 after consultation with Math Dept)
AB 3114 or 120: attend Math Advising Session
AB 1 or 2Take Calculus Placement Exam
IB Exam ScoreWhich Math course to take
IB 6 or 7150, 210, 212, or 214.
IB 5114 or 120 or 128: attend Math Advising Session
IB 4114
IB 3 or lessTake Calculus Placement Exam

In addition to the calculus courses, Mathematics 105, 146, 150, 160, 210, 212, 214, and Computer Science 211 may be taken by first-year students meeting the prerequisites.

Students with transfer credits should confer with the Department for advice on placement in an appropriate mathematics course.

STATISTICS PLACEMENT: Students receiving a 4 or 5 on the AP Statistics Exam are exempt from Math 146; Math 150 is recommended for these students wanting to take further statistics courses.

MATHEMATICS COURSES: Calculus is a prerequisite for all mathematics courses with the exceptions of Mathematics 105 and 146, as well as for most Computer Science courses. All students planning to take Calculus must take the online Calculus Placement Exam prior to the beginning of the Fall Semester unless they are exempt due to having received an Advanced Placement exam score. (See Calculus Placement above or contact the Mathematics Department for further details.) Prerequisites for any course may be waived with permission of the instructor.



Mathematics Courses

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104 - Women in Mathematics

This course is designed to introduce a variety of mathematical topics stemming from the research of women mathematicians both past and present, from Hypatia to current professors. In discussing the work of these women, we will also discuss the gender issues that are associated with being a female mathematician. Course material will be covered in lecture, research, in-class visitors and activities. Course work will include research papers, a course project and problem sets related to the mathematician of discussion.

105 - Mathematics as a Liberal Art

Introduction to mathematical thinking. Investigation of mathematical patterns in counting, reasoning, motion and change, shape, symmetry, and position. Not open to seniors.


Calculus differs in some respects from the traditional courses offered at some secondary schools and most other colleges or universities. Occidental's program is based on scientific modeling, makes regular use of computers, and requires interpretation as well as computation. A variety of courses comprise this program, accommodating different levels of preparation. The core content is described below as Calculus 1 and 2. Actual courses suited to different levels of preparation are listed under each description.

Calculus 1: Scientific Modeling and Differential Calculus
Many mathematical models in the natural and social sciences take the form of systems of differential equations. This introduction to the calculus is organized around the construction and analysis of these models, focusing on the mathematical questions they raise. Models are drawn from biology, economics, and physics. The important elementary functions of analysis arise as solutions of these models in special cases.

The mathematical theme of the course is local linearity. Topics include the definition of the derivative, rules for computing derivatives, Euler's Method, Newton's Method, Taylor polynomials, error analysis, optimization, and an introduction to the differential calculus of functions of two variables.

CALCULUS 2: Scientific Modeling and Integral Calculus
This course continues the study of the calculus through scientific modeling. While Calculus 1 is concerned with local changes in a function, Calculus 2 focuses on accumulated changes. Models solved by accumulation functions lead to the definition of the integral and the Fundamental Theorem of Calculus.

Additional topics include numerical and analytic techniques of integration, trigonometric functions and dynamical systems modeling periodic or quasiperiodic phenomena, local approximation of functions by Taylor polynomials and Taylor series, and approximation of periodic functions on an interval by trigonometric polynomials and Fourier series.

108 - Unified Precalculus and Calculus 1-A

The first of a two course sequence enriching the material in Calculus 1 with additional study of elementary functions, algebra, trigonometry, graphing, and mathematical expression. Weekly lab. Prerequisites: the Calculus Readiness Examination and less than four years of high school mathematics. 

109 - Unified Precalculus and Calculus 1-B

Continuation of Mathematics 108. This course satisfies Calculus 1 prerequisites for subsequent courses. Weekly lab. Prerequisite: Mathematics 108.

110 - Calculus 1

This course satisfies Calculus 1 prerequisites for subsequent courses. Weekly lab. Prerequisites: the Calculus Readiness Examination and at least four years of high school mathematics.

114 - Calculus 1 (Experienced)

This course satisfies Calculus 1 prerequisites for subsequent courses. Weekly lab. Prerequisites: a year of prior calculus experience and either the Calculus Readiness Examination or an appropriate Advanced Placement Calculus score.

120 - Calculus 2

This course satisfies Calculus 2 prerequisites for subsequent courses. Weekly lab. Prerequisites: Mathematics 109 or 110 or 114.

128 - Calculus 2 (Advanced Placement)

A one-semester course focusing on infinite sequences and series, including power series and Taylor series. More advanced topics will be chosen by the professor, which may include techniques for solving differential equations, mathematical modeling, Fourier Series, the Laplace Transform, and the Fourier Transform. The course assumes mastery of the basic skills, particularly integration techniques and differentiation rules, from the successful completion of Advanced Placement (AB) calculus. This course satisfies Calculus 1 and Calculus 2 prerequisites for subsequent courses. Weekly lab. Prerequisite: permission of instructor or AP Calculus AB score of 4 or 5.

146 - Statistics

Comprehensive study of measures of central tendency, variation, probability, the normal distribution, sampling, estimation, confidence intervals and hypothesis testing. Introduction to use of technology in statistics. Real-life problems are used to illustrate methods. Weekly lab. Not open to students who have completed or are currently enrolled in Psychology 201, Biology 368, Mathematics 150, or any Mathematics course above 200.

150 - Statistical Data Analysis

An introductory course in statistics emphasizing modern techniques of data analysis. Exploratory data analysis and graphical methods; random variables, statistical distributions, and linear models; classical, robust, and nonparametric methods for estimation and hypothesis testing; introduction to modern multivariate methods. Students will make significant use of a computer application specifically designed for data exploration. The course is strongly recommended for students who are going to use graphical techniques and statistics for research in their fields. Weekly lab. Prerequisite: a Calculus 1 course or permission of instructor.

160 - Creative Problem-Solving

Formal and informal techniques for problem-solving, developed by working on an intriguing collection of puzzles and problems which go beyond those encountered in the usual curriculum. These include problems which can be posed in elementary mathematical or logical terms but which require strategy and ingenuity to solve. Prerequisite: a genuine desire to solve problems!
2 units

186 - Network Models

This course treats network and graphical models arising especially in biological and cognitive sciences. Methods include networks, graphs, and matrices; probability, conditional probability, and Markov chains; discrete-time dynamics and recurrent neural networks; Bayesian statistical inference on graphical models; and optimization on graphs, including dynamic programming. In the computing laboratory component (a separately-scheduled 1.5 hour session), students will learn to use MATLAB to build and analyze models. Students will complete projects in each major area of the course. Calculus is not a pre-requisite. While open to all students, this course is intended as an alternative to calculus as a first course in college-level mathematics.

195 - Directed Research in Mathematics

Intensive study in an area of mathematics or computer science of the student's choosing under the direct supervision of a member of the faculty. Prerequisite: permission of the supervising instructor. May be repeated once for credit.
1 unit

201 - Mathematics, Education, and Access to Power

This seminar course is a writing-intensive Community Based Learning based course designed to expose students to the complicated ways that mathematics affects the community. The CBL component of this course involves tutoring and mathematics assistance at Franklin High School in nearby Highland Park. The seminar component involves meeting weekly with processing discussions and discussion of readings. Topics will include the teaching and learning of mathematics as well as the role of mathematics in individuals' lives and their community. May be taken twice for credit.
2 units

210 - Discrete Mathematics

The language of sets and logic, including propositional and predicate calculus. Formal and informal proofs using truth tables, formal rules of inference and mathematical induction. Congruences and modular arithmetic. Elementary counting techniques. Discrete probability. Abstract relations including equivalence relations and orders. Prerequisite: a Calculus 2 course.

212 - Multivariable Calculus

Calculus of functions of several variables, parametric curves and surfaces, and vector fields in 2- and 3-space, with applications. Vectors, graphs, contour plots. Differentiation, with application to optimization. Lagrange multipliers. Multiple and iterated integrals, change of variable and the Jacobian. Line and surface integrals. Vector analysis, Green's, Gauss', and Stokes' Theorems. Applications to physics, economics, chemistry, and mathematics. Prerequisite: a Calculus 2 course.

214 - Linear Algebra

Introduction to basic concepts of linear algebra through the study of linear algebraic systems and matrix algebra.  Topics include an introduction to planes and lines, vector operations, subspaces, Gaussian elimination, linear independence, invertibility of matrices, orthogonality, matrix operations, eigenvalues and eigenspaces. The course stresses definitions and mathematical proof.. Prerequisite: a Calculus 2 course.

295 - Topics in Mathematics

Topics in mathematics, selected largely by student interest and faculty agreement. Prerequisite: a Calculus 2 course or permission of instructor.
2 or 4 units

300 - Junior Colloquium

Preparation for the comprehensive examination and senior project. Completion of Third Year Writing Requirement. Emphases on problem-solving, clear written expression and verbal presentation. Open to junior mathematics majors.
2 units

310 - Real Analysis

A beginning course in advanced calculus and real analysis. Properties of the real number system, sequences and series of real numbers, the Heine-Borel and Bolzano-Weierstrass Theorems, continuity and uniform continuity, sequences and series of functions. Prerequisite: Mathematics 210.

312 - Complex Analysis

The differential and integral calculus of complex-valued functions of a complex variable, emphasizing geometry and applications. The complex number system, analytic functions and the Cauchy-Riemann equations, elementary functions and conformal mappings, contour integration, Taylor and Laurent series, function theory. Applications to physics, engineering and real analysis. Prerequisite: Mathematics 212.

320 - Algebra

A first course in group theory: basic axioms and theorems, subgroups, cosets, normal subgroups, homomorphisms, and extension of the theory to rings and fields. Prerequisites: Mathematics 210 and 214.

322 - Number Theory

Classical theory of numbers, from ancient to modern. Prime numbers and factorization. Divisors, numerical functions, linear and quadratic congruences. Diophantine problems, including the Fermat conjecture. Factoring methods. Prerequisite: Mathematics 210.

330 - Probability

Standard methods of calculus are used to study probability: sample spaces, random variables, distribution theory, estimating unknown parameters of distributions. Various applications to real life problems will be discussed. Moment-generating functions and other techniques to calculate moments and characterize distributions. Probabilistic inequalities and the central limit theorem. Point estimators and unbiasedness. Prerequisites: Mathematics 212 and 214.

332 - Mathematical Statistics

Theory and applications of statistical inference. Both Bayesian and classical parametric methods are considered. Point and interval estimation, hypothesis testing. Limit theorems and their use in approximation, maximum likelihood estimation and the generalized likelihood ratio test. Introduction to linear models, nonparametric methods, and decision theory. Prerequisite: Mathematics 330.

340 - Ordinary Differential Equations

This course will focus on theoretical, qualitative, and quantitative analyses of ordinary differential equations from a modern perspective using analytical, graphical, and numerical points of view. Topics can include first-order linear and nonlinear differential equations, first order linear systems, second-order linear differential equations, autonomous differential equations and their bifurcations, boundary value problems, solutions using infinite series, Laplace transforms and various numerical approximation techniques. Prerequisite: Mathematics 212 and 214 or permission of instructor.

342 - Partial Differential Equations

An introduction to the study of partial differential equations. This course will include the study of Fourier series, the separation of variables methods, and specifically the wave, heat and Laplace's equations as well as other elementary topics is PDEs. Numerical approximation techniques and applications to specific topics such as traffic flow, dispersive waves or other areas may be included. Given in alternate years.
Prerequisite: Mathematics
212, 214 and 341

350 - Mathematical Logic

A metamathematical investigation of the main formal language used to symbolize ordinary mathematics: first order logic. The focus is on the two fundamental theorems of logic: completeness and compactness. Gödel's completeness theorem says that every intuitively valid consequence is formally provable from the hypotheses, while compactness says that every intuitively valid consequence of an infinite premise set really depends on only finitely many premises. Prerequisite: Mathematics 210 or permission of instructor. Given in alternate years.

352 - Computability and Complexity

The logical foundation of the notion of a computable function underlying the workings of modern computers. Representation of the informal mathematical idea of calculability by canonical proxies: "general recursive functions," "Turing computable functions." Discussion of Church's Thesis, which asserts the adequacy of these representations. Survey of decidable and undecidable problems. Prerequisites: Mathematics 210 or permission of instructor.

354 - Set Theory and Foundations of Mathematics

Cantor's naïve theory of sets and equinumerosity. Paradoxes and axiomatic set theory. Finite and infinite cardinal numbers, fixed point theory, applications to computer science. Well orderings, transfinite induction and recursion, the Axiom of Choice and its consequences, ordinal numbers and the cumulative hierarchy of sets. Discussion of the Continuum Hypothesis and its relation to models of set theory. Prerequisites: Mathematics 210 or permission of instructor.

360 - Axiomatic Geometry

Axiomatic development of Euclidian and non-Euclidian geometries, including neutral and hyperbolic geometries, and, possibly, brief introductions to elliptic and projective geometries. The course will emphasize a rigorous and axiomatic approach to geometry and consequences of Euclid's Parallel Postulate and its negations. Prerequisite: Mathematics 210 or permission of instructor.

362 - Topology

General topology studies those properties (such as connectedness and compactness) which are preserved by continuous mappings. A disk and a solid square are topologically equivalent; so are a doughnut and a coffee cup; but a disk is different from a doughnut. This course enables you to construct your own proofs and counterexamples while getting to know the basic concepts behind modern mathematics. Prerequisites: Mathematics 210, and Mathematics 212 or 214, or permission of instructor.

370 - Numerical Analysis

This is a first course in studying numerical techniques in solving a variety of problems in mathematics using computer algorithms. Topics can include methods for approximating solutions to algebraic equations, iterative methods for linear and nonlinear systems, interpolation and approximation theory, numerical integration, explicit and implicit methods for solving initial value problems and boundary value problems. Error estimation, stability and performance are themes throughout. Students will be expected to be able to execute standard algorithms using a computer programming language by the end of the course. Prerequisite: Mathematics 212 and 214 or permission of instructor. Prerequisite: Mathematics 212 and 214 or permission of instructor.

372 - Operations Research

Optimal decision-making and modeling of deterministic and stochastic systems. Different systems of constraints lead to different methods. Linear, integer, dynamic programming, and combinatorial algorithms. Practical problems from economics and game theory. Inventory strategies and stochastic models are analyzed by queuing theory. Prerequisites: Mathematics 210 and 214.

380 - Combinatorics

Investigation of the existence and classification of arrangements. Topics to include principles of enumeration, inclusion-exclusion, the pigeon-hole principle, Ramsey theory, generating functions, special counting sequences, and introductory graph theory. Prerequisite: Mathematics 210.

382 - Graph Theory

Graph Theory is a beautiful area of mathematics with many applications. It is used in computer science, biology, urban planning, and many other contexts. Like other areas of discrete mathematics, Graph Theory has the property that the problems are often quite approachable and understandable. Sometimes the solutions to Graph Theory problems can be complex and often require clever arguments, thus the subject is quite pleasing to study. This class will build a solid foundation in Graph Theory for the students. Possible topics are graph isomorphisms, coverings, and colorings; independence number, clique number, connectivity, network flows, and matching theory. Prerequisite: Mathematics 210. Suggested co-requisite: Mathematics 380.

392 - Mathematical Models in Biology

This course is intended to introduce students to common models used in biology. A variety of models in terms of both biology and mathematics will be covered. Biological topics include action potential generation, genetic spread, cell motion and pattern formation, and circulation. These topics span a range of mathematical models as well, including finite difference equations and differential equations, both linear and non-linear. The focus will be on model analysis and the translation between the mathematical language and the biological meaning. Such analysis will be done both quantitatively and qualitatively. Towards this end, topics seen in previous mathematical courses, such as eigenvalues, phase portraits, and stability, will be revisited. Relevant biology will be presented with each model. The course will be project based. Prerequisite: Mathematics 212 and 214, or permission of instructor.

395 - Special Topics in Advanced Mathematics

Special topics in advanced mathematics, selected largely by student interest and faculty agreement. May be repeated for credit.

Advanced Differential Equations. The course will consists of advanced topics in differential equations not usually seen in either ordinary differential equations or partial differential equations such as delay differential equations, stochastic differential equations. boundary value problems, numerical methods, and infinite series solutions. Prerequisite: Math 340 or Math 342 or permission of instructor.

Knot Theory. An introduction to Knot Theory: how knots are described mathematically, how one can distinguish different knots, create new knots, classify knots. Topics include: Reidemeister moves, links, knot colorings, alternating knots, braids, knots and graphs, knot invariants, mirror images, unknotting number, crossing number, applications to biology and chemistry. Prerequisite: Math 210, Math 212 or Math 214 or permission of instructor.

Computational Differential Geometry. Differential geometry combines calculus, algebra and geometry. It is an important tool in the simulation and analysis of nonlinear objects. The focus of this course is extrinsic and intrinsic analysis of curves and surfaces. Topics include differential forms, frame fields, the shape operator, Gaussian and mean curvature, the Gauss-Bonnet Theorem, and geodesics. Applications to computer graphics, image processing, statistics, differential equations and physics. The computational component uses Mathematica, but no prior knowledge of Mathematica is assumed. Prerequisite: Math 212 and Math 214, or permission of the instructor.

396 - Mathematical Modeling

A project-oriented introduction to mathematical modeling. Techniques from calculus, linear algebra and other areas of mathematics will be used to solve problems from the life, physical and social sciences. Familiarity with a programming language is desirable but not required. This course may be taken up to two times for credit. Prerequisites: Mathematics 212 and 214.
2 units

397 - Independent Study in Mathematics

Directed individual study of advanced topics. Prerequisite: permission of instructor.
2 or 4 units

400 - Senior Colloquium in Mathematics

Senior comprehensive projects. Required of senior mathematics majors.
2 units

499 - Honors in Mathematics

Students who have been accepted by the Department to do honors should register for Math 499 in lieu of  Math 400.
Prerequisite: permission of department.


Regular Faculty

Alec Schramm, chair

Professor, Physics

B.A., Cornell University; M.A., Ph.D., Duke University

Treena Basu

Assistant Professor, Mathematics

B.S. Jogamaya Devi College: University of Calcutta; M.S. University of Texas-Pan American; M.S. Bengal Engineering and Science University; Ph.D. University of South Carolina

Ron Buckmire

Professor, Mathematics

B.Sc., M.Sc., Ph.D., Rensselaer Polytechnic Institute

Alan Knoerr

Associate Professor, Mathematics, Cognitive Science

B.A., Oberlin College; Sc.M., Ph.D., Brown University

Tamás Lengyel

Professor, Mathematics

Diploma, Ph.D., Eotvos University, Budapest

Eric Sundberg

Associate Professor, Mathematics

A.B., Occidental College; Ph.D., Rutgers University

Nalsey Tinberg

Professor, Mathematics

B.A., UCLA M.S.; Ph.D., University of Warwick

Gregory Tollisen

Full-Time Non-Tenure Track Professor, Mathematics

B.S., University of Portland; M.S., Caltech

Ramin Naimi

Professor, Mathematics

B.S., UCLA; Ph.D., Caltech

On Special Appointment

Kanadpriya Basu

Part-Time Non-Tenure Track Assistant Professor, Mathematics

B.Sc. Presidence College, University of Calcutta; M.Sc. Bengal Engineering and Science University; M.S. University of Texas-Pan American; Ph.D. University of South Carolina

Gerald Daigle

Non-Tenure Track Assistant Professor, Mathematics

B.A. Pomona College; M.A. Cambridge University; Ph.D. California Institute of Technology

Nishu Lal

Full-Time Non-Tenure Track Assistant Professor

B.S., M.S., UC, Irvine; Ph.D., UC Riverside

Don Lawrence

Full-Time Non-Tenure Track Professor

B.A., Pomona College; M.A., Ph.D., UC Santa Barbara

Jeffrey Miller

Full-Time Non-Tenure Track Assistant Professor

B.S. UC Davis; M.A., Ph.D., UC Santa Barbara