38 courses with the subject MATH H, 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.
MATH H103INTRODUCTION TO PROBABILITY AND STATISTICS1.0
Basic concepts and methods of elementary probability and quantitative reasoning, with practical applications. Topics include: sample average and standard deviation, normal curves, regression, expected value and standard error, confidence intervals and hypothesis tests. Crosslisted: Mathematics, Statistics Prerequisite(s): Not open to students who have (a) placed into 120 or higher, (b) taken 118 or higher, (c) taken any other introductory statistics class at Haverford or Bryn Mawr, (d) received a score of 4 or 5 on the AP Statistics exam
An introduction to aspects of calculus useful in applied work in the natural and social sciences, with a strong emphasis on developing mathematical modeling skills. Topics include differential and integral calculus of functions of one variable, multivariable optimization, and modeling with differential equations. Applications to biology, economics, and physics. This course is taught at the level of a beginning calculus course, and no prior calculus experience is assumed. Prerequisite(s): Not open to students placing into MATH 118 or higher or Math 105 cannot be taken by students who have AP credit for calculus or with previous calculus credit, except with instructor consent
MATH H110INTRODUCTION TO THE MATHEMATICAL SCIENCES: DATA, MODELS, AND FUNCTIONS1.0
Exploration of key ideas of statistics, mathematics, and applications, introducing students to differential calculus and the core areas of our department and major. Students will work with data and learn ways to summarize its features and visualize its structure. Students will work with mathematical definitions of certain structures (possibly including a symmetry or modeling real-world discrete processes) and perform computations within these structures to allow them to formulate conclusions or conjectures. Pre-requisite(s): None. Anti-requisite: MATH 120 or 121, or placement into MATH 120 or 121 or higher. Lottery Preference: Reserve 16 spaces for first years
A study of the evolution of systems defined by difference and differential equations. Methods of analysis come from calculus: the limit, the derivative, and the integral from numerical, graphical, and symbolic perspectives. Not open to students placing into Math 121 or higher, except with instructor permission. Prerequisite(s): MATH 105 or placement. Not open to students with credit for MATH B102 (Calculus II) or equivalent, except with instructor consent
MATH H120MULTIVARIABLE CALCULUS: OPTIMIZATION AND PROBABILITY1.0
A course covering multivariable derivatives (with a focus on optimization) and single- and multivariable integrals (with a focus on probability). Pre-requisite(s): MATH 110 or 105, or placement, or instructor consent. Antirequisite: MATH 121 already taken or placed past. Lottery Preference: Reserve 16 spaces for first years
An introduction to functions of several variables, vector geometry, partial derivatives, optimization, Taylor’s Theorem, multiple integrals, line integrals, and Green’s and Stokes’ Theorems. Prerequisite(s): MATH 118 or equivalent placement, or instructor consent. Not open to students who have previously taken multivariable calculus at the college level, either at Haverford or elsewhere, except with instructor consent
MATH H146ETHICS AND THE USE OF MATHEMATICS, WITH A FOCUS ON ANTI-RACISM0.5
This half-credit seminar will explore what it means to “do math ethically”, to emphasize the ways in which mathematics is inherently political, and to think about anti-racism in mathematical disciplines. This course is graded P/F. Crosslisted: Independent College Programs, Mathematics
MATH H203STATISTICAL METHODS AND THEIR APPLICATIONS1.0
An introduction to statistical methods used to analyze data in the natural and social sciences. It covers descriptive statistics, the binomial and normal distributions, expected value and variance, confidence intervals and hypothesis testing, comparison of two samples, regression, and analysis of variance. Crosslisted: Mathematics, Statistics Prerequisite(s): MATH 110 or higher, placement into MATH 120 or 121 or higher, or instructor consent. Students who have taken another introductory statistics course at Haverford or Bryn Mawr may only enroll in STAT 203 with instructor consent.
An introduction to the theory of ordinary differential equations (ODEs) including algebraic techniques for solving a single ODE or a linear system of ODEs, numerical techniques for generating approximate solutions, geometric techniques for displaying solutions to understand their behavior, analyzing nonlinear systems, and some key theorems (such as existence and uniqueness of solutions). The focus of this course will be on applications of the methods and solving real systems. Prerequisite(s): MATH 120 or 121 or MATH 215 (or 216) or consent of instructor.
An introduction to the optimization of a linear function subject to linear constraints, with applications that include game theory, transportation problems, and network flows. The course includes some theoretical material on the properties of these linear optimization problems, and also a strong emphasis on algorithms, especially the simplex method and some enhancements to it (which are especially relevant since many applications involve many variables and many constraints). Crosslisted: Mathematics, Computer Science, Economics Prerequisite(s): Co-requisite of MATH 120 or 121 or MATH 215, or equivalent placement, or instructor consent.
An abstract introduction to linear algebra, focusing on proof techniques. Topics covered include: vector spaces, linear transformations and matrices, determinants, eigenvalue problems, quadratic forms, and the spectral theorem. Prerequisite(s): MATH 120 or 121 or equivalent placement, or CMSC 231. Lottery Preferences: Reserve 8 spaces for first-years, then Math/Stat majors, then Math/Stat minors, then Sophomores
Advanced calculus and geometry of multivariable functions and vector fields. Multivariable functions will be analyzed using generalizations of the derivative and the integral. Vector fields will be investigated using the divergence, gradient, and curl as well as line and surface integrals, parametrized surfaces, and generalizations of the Fundamental Theorem of Calculus in the form of Green's, Gauss', and Stokes' Theorems. Applications to geometry and, to a lesser extent, physics will be discussed. Prerequisite(s): Math 120 or 121, 5 on the Calculus AB exam, a 4 or 5 on the Calculus BC exam, or instructor permission
An introduction to probability theory. Topics include: sample spaces, combinatorics, conditional probability, independence, discrete and continuous random variables, functions of random variables, expected value and variance, the moment generating function, and some basic limit theorems. Prerequisite(s): MATH 120 or 121 or MATH 216, or instructor consent.
MATH H222SCIENTIFIC COMPUTING: CONTINUOUS SYSTEMS1.0
A survey of major algorithms in modern scientific computing, with a focus on continuous problems. Topics include numerical differentiation and integration, numerical linear algebra, root-finding, optimization, Monte Carlo methods, and discretization of differential equations. Basic ideas of error analysis are presented. A regular computer lab introduces students to the software package Matlab, in which the algorithms are implemented and applied to various problems in the natural and social sciences. Prerequisite: MATH 120 or 121. Cross-listed: Mathematics, Computer Science
Quantitative methods for measuring health disparities. Statistical and mathematical tools for investigating health outcomes will be considered, with a particular eye towards social impact. One to two hours per semester of co-curricular seminar attendance encouraged. Pre-requisite(s): An introductory course in statistics (STAT 203, ECON 203 or 204, PSYC 200, SOCL 215, or statistics placement past STAT 203) and introductory calculus exposure (MATH 110 or placement past 110), or instructor permission. Lottery Preference: Reserve 8 spaces for first-years, then Health Studies minors, then Math/Stat majors, and then Math/Stat minors.
A 200-level course in mathematics, with the topic varying each time it is offered. See course notes for descriptions, prerequisites, and lottery preferences.
MATH H299JUNIOR SEMINAR IN MATHEMATICS AND STATISTICS1.0
A course to introduce all math majors to research and communication methods used by mathematicians and statisticians, and to discuss the structures and workings of mathematical communities, including the ethical implications of bringing mathematical skills to a workplace or community. Students produce a “junior paper” anchored in an application of linear algebra, helping prepare them to write a thesis as a senior, and plan a colloquium or panel discussion open to the entire Haverford community. Pre-requisite(s): Linear Algebra (MATH H215) or instructor consent Lottery Preference: Math Majors, by seniority within that group
A rigorous development of topics in calculus, including the axioms of the real number line, cardinality, convergence of sequences, point-set topology (open/closed sets, compactness, connectedness), continuity, differentiability, and the Riemann integral. The course also has a major focus on the writing of clear and correct mathematical proofs. Prerequisite(s): MATH 215 and MATH 120 or 121 or 216, or instructor consent. Lottery Preferences: Math/Stat majors, then Math/Stat minors, then Sophomores
An introduction to mathematical theory of statistics. Topics include: Estimation, Hypothesis Testing, one-sample inference, two-sample inference, and regression. Additional topics may include: goodness-of-fit tests and analysis of variance. Crosslisted: Mathematics, Statistics Prerequisite(s): MATH 218
A rigorous treatment of fundamental algebraic structures. Topics include: introduction to groups, modular arithmetic, polynomials, rings, fields, Galois theory, vector spaces, and modules. Prerequisite(s): MATH 215 and MATH 120 or 121 or 216, or instructor consent.
Generalizes topological concepts from Euclidean spaces to arbitrary topological spaces, and introduces elements of algebraic topology. Concepts covered include continuity, connectedness, and compactness. The course culminates in an exploration of the fundamental group and covering spaces. Prerequisite(s): MATH 215 and MATH 120 or 121 or 216, or instructor consent.
A study of the differential geometry of curves and surfaces. Concepts covered include both the local theory (including metrics, curvature, and geodesics) and the global theory, including the Gauss-Bonnet theorem. Prerequisite(s): MATH 317 or MATH 216 with special permission, or instructor consent
Qualitative and quantitative analysis of algorithms and their corresponding data structures from a precise mathematical point of view. Performance bounds, asymptotic and probabilistic analysis, worst case and average case behavior. Correctness and complexity. Particular classes of algorithms such as sorting searching will be studied in detail. Crosslisted: Computer Science, Mathematics Prerequisite(s): CMSC 106 or 107 or B206, and 231, or instructor consent
Introduction to the mathematical foundations of computer science: finite state automata, formal languages and grammars, Turing machines, computability, unsolvability, and computational complexity. Attendance at the weekly discussion section is required. Crosslisted: Computer Science, Mathematics Prerequisite(s): (CMSC 106, 107, 151, or 206) and CMSC 231, and junior or senior standing, or instructor consent
MATH H361APPLIED MULTIVARIATE STATISTICAL ANALYSIS1.0
An introduction to multivariate statistical analysis. The course includes methods for choosing, fitting, and evaluating multiple regression models and analysis of variance models. A required computer lab, using R, is taught alongside this course. Crosslisted: Mathematics, Statistics Prerequisite(s): MATH 215 and one of the following: ECON 204, MATH 203, PSYC 200, SOCL 215
MATH H382MATHEMATICAL MODELING AND DIFFERENTIAL EQUATIONS1.0
An introduction to modeling in applied mathematics using differential equations, with examples from biology, chemistry, engineering, physics, and/or the social sciences. Through these examples, we build mathematical models that reflect real world scenarios and analyze them to gain an understanding of the problem. Techniques of analysis may include phase plane methods, stability analysis, bifurcation theory, and computer simulation. Pre-requisite(s): MATH H204 or equivalent, or permission of the instructor Lottery Preference: Math majors, then math minors, then by seniority
This course is an introduction to partial differential equations, involving a mix of (1) analysis (the use of various tools to ask questions of existence and uniqueness of solutions and, in special cases, find solutions), (2) computation (the development of numerical techniques to find approximate solutions on the computer), and (3) modeling (the connection of mathematics to real problems). The balance of these features will vary from instructor to instructor. Pre-requisite(s): MATH H204 or equivalent, or instructor permission Lottery Preference: Math majors, then math minors, then by seniority
MATH H384CONSTRAINED AND COMBINATORIAL OPTIMIZATION1.0
This course explores two different types of challenging optimization problems: those with constraints, and those with search spaces so large that methodical explorations tend to be impractical. In the first phase of the course, we study constraints of three different types: equality, inequality, and integer. In the second phase, we focus on algorithms that use randomness to effiiciently explore large spaces in search of an optimum. Pre-requisite(s): An introductory coding course (including MATH/CMSC/ECON 210, MATH/CMSC 222, or CMSC 105) or permission of the instructor. Lottery Preference: Math majors, then math minors, then by seniority
MATH H390ADVANCED TOPICS IN ALGEBRA: COMMUTATIVE ALGEBRA1.0
A 300-level course in algebra, with the particular topic(s) varying each time it is offered. Fall 2025: Commutative Algebra. Topics from commutative ring theory, including techniques of localization, prime ideal structure in commutative Noetherian rings, Chinese Remainder Theorem, Zariski Topology, exact sequences and classes of modules; discussion will also involve using the software Macaulay 2 for computing examples. Prerequisite: MATH 333 or another first course in abstract algebra, or permission of instructor
MATH H392ADVANCED TOPICS IN ANALYSIS: COMPLEX ANALYSIS1.0
A 300-level course in analysis, with the particular topic(s) varying each time it is offered. Spring 2026: Complex Analysis, including the algebra and geometry of complex numbers, analytic functions, complex integration (including the Cauchy integral formula and the calculus of residues), and conformal mappings (including, hopefully, the Riemann Mapping Theorem). Prerequisite: MATH 317 or permission of instructor
MATH H394ADVANCED TOPICS IN THEORETICAL COMPUTER SCIENCE: INTRODUCTION TO DISCRETE MATHEMATICS1.0
A 300-level course on the mathematical foundations of computer science, with the particular topic(s) varying each time it is offered. Fall 2026: This course introduces three fundamental aspects of discrete mathematics: enumeration, graph theory and discrete probability. Our introduction to enumeration covers basic counting, basic approximations, bijective arguments, double-counting arguments, recurrence relations, generating functions, the pigeonhole principle, inclusion-exclusion, etc. Our introduction to graph theory includes topics such as connectivity, trees, matchings, colorings, Ramsey theory, etc. Our introduction to discrete probability includes linearity of expectation, the law of averages, Markov's inequality, Chebyshev's inequality, etc. We will see how discrete probability can be used to prove the existence of surprising discrete structures. Prerequisites: Math 120 and Math 215, and a solid grasp of proof techniques Crosslisted: Mathematics, Computer Science
MATH H396ADVANCED TOPICS: PROBABILITY AND STATISTICS1.0
A 300-level course in probability and/or statistics, with the particular topic(s) varying each time it is offered. Spring 2025: The main topics for this course are nonparametric methods and categorical data analysis. Students will learn nonparametric statistical tests in one-sample, two-sample and k-sample situations as well as basic categorical data analysis. Crosslisted: Mathematics, Statistics. Prerequisite(s): MATH 218 and one of the following: MATH 203, ECON 203/204, PSYC 200, SOCL 215 or instructor permission
MATH H397ADVANCED TOPICS IN APPLIED MATHEMATICS: MATHEMATICAL BIOLOGY1.0
A 300-level course in applied mathematics, with the particular topic(s) varying each time it is offered. Prerequisite(s): MATH 120 or 121 and MATH 215, or instructor consent.
Students work as assistants to a faculty member in an introductory mathematics course for a semester, offering various kinds of classroom support including problem sessions, review, tutoring, and laboratory assistance. Open to junior and senior majors by arrangement with the faculty member in question. May be taken at most twice.
