Mathematics Course Descriptions

This course will cover properties of real numbers, linear equations and inequalities, systems of linear equations, factoring, polynomials, rational and radical expressions, exponentials and logarithms. Students will complete regular reading and writing assignments as well as in-class assessments.

An exploration of functions, including polynomial, rational, exponential, logarithmic, and trigonometric functions. This course is designed to prepare students for the study of calculus at Lawrence. PREREQUISITES: Minimum score on ALEKS diagnostic exam, as set by the department.

For students in all disciplines. Provides the background needed to evaluate statistical arguments found in newspapers, magazines, reports, and journals and the logic and techniques necessary to perform responsible elementary statistical analysis. Topics include basic data analysis, one-variable regression, experimental and sampling design, random variables, sampling distributions, and inference (confidence intervals and significance testing). This course may not be taken on a Satisfactory/Unsatisfactory basis. Students with credit for MATH 140 or equivalent, or BIOL 170, or AP Statistics should not take this course and should instead consider STAT 255.

Functions, limits, derivatives, the Mean Value Theorem, definition and properties of integrals, the Fundamental Theorem of Calculus, and applications to related rates, curve sketching, and optimization problems. PREREQUISITES: Minimum score on ALEKS online diagnostic exam, as set by the department.

Techniques of integration, vector algebra in the plane and space, matrix algebra, functions of several variables, partial derivatives, double and triple integration, optimization. PREREQUISITES: MATH 140 or suitable AP or IB score and minimum score on ALEKS online diagnostic exam as set by department

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Complex numbers, sequences, convergence, series, power series, additional topics chosen from analysis, geometry, differential equations, and applied mathematics PREREQUISITES: MATH 155

An introduction to programming with emphasis on learning from data in order to gain useful insights. Topics focus on elementary programming concepts in the R language and the necessary tools to handle, analyze and interpret data. This course will be taught in a workshop format, and students will complete regular assignments and a final project that provide hands-on programming/analysis experiences. PREREQUISITES: One prior course MATH, STAT, or CMSC course, or BIOL 170, or BIOL 280, or consent of instructor

An overview of techniques used to discover structural patterns and make predictions using complex datasets that are prevalent in today's world. The central machine learning tasks of classification, clustering, and regression will be explored, along with methods for training models and evaluating predictions. This course will be taught in a workshop format. Assignments will involve the use of statistical software. PREREQUISITES: CMSC 150, or CMSC 205, or CMSC 210, or consent of instructor

Students will learn ways to aid decision-making by applying a scientific approach to decision problems involving quantitative factors: defining the problem, gathering data, formulating a model of the problem, developing computer-based procedures for evaluating solutions, testing and refining the model, analyzing the model’s alternatives, and communicating the results. Many assignments and exams will be completed using Excel, so students will also gain advanced Excel skills. PREREQUISITES: Sophomore standing

QDM2 picks up where QDM leaves off, asking students to create solutions more autonomously and examining more complex decision problems. For example, we may examine nonlinear optimization with multiple decision variables and more complex decision-making under uncertainty, including the use of simulation models, probability distributions, and Bayes Rule. Many assignments and exams will be completed using Excel, building on the Excel skills developed in QDM. PREREQUISITES: Econ 223 and STAT 255, or Econ 223 and instructor approval

An introduction to mathematical reasoning and proof in the context of discrete structures relevant to the study of computer science. Topics include induction, sets, relations and functions, graph theory, combinatorics, and probability. PREREQUISITES: MATH 155

The study of vector spaces, linear transformations, matrices, and applications. Topics include linear independence, dimension, rank-nullity, change of basis, eigenvectors and eigenvalues, determinants, and inner products. PREREQUISITES: MATH 200

This course introduces modern statistical techniques in the context of predictive inference and modeling. Topics will include data analysis techniques such as linear and logistic regression, ANOVA, nonparametric methods, and computational approaches such as cross-validation and bootstrapping. Statistical software will be used frequently. This class will involve regular in-class and out-of-class assignments as well as exams and quizzes. PREREQUISITES: STAT 107, BIOL 170, BIOL 280, or MATH 140, or instructor permission

An introduction to probability and its applications. Topics will include combinatorial and axiomatic probability, conditional probability and Bayes' Theorem, random variables, expectation and variance, discrete and continuous probability distributions, joint and conditional distributions, and limit laws. PREREQUISITES: MATH 200, and either MATH 220 or MATH 230

An introduction to probability and its applications. Topics will include combinatorial and axiomatic probability, conditional probability and Bayes' Theorem, random variables, expectation and variance, discrete and continuous probability distributions, joint and conditional distributions, and limit laws. PREREQUISITES: MATH 200, and either MATH 220 or MATH 230

A study of ordinary differential equations and applications. Topics include standard techniques for special types of equations, linear and non-linear systems, existence and uniqueness, and qualitative behavior. PREREQUISITES: MATH 250

Advanced work in mathematics on topics not covered in regular offerings. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Advanced work in statistics on topics not covered in regular offerings. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

The academic component of the internship includes readings related to the substance of the internship, discussions with the faculty supervisor, and a written report appropriate to the discipline. Course grades are based on this academic work.

Guided independent study of an advanced topic in undergraduate mathematics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Guided independent study of an advanced topic in undergraduate statistics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

A survey of techniques used in modeling physical systems, with particular emphasis on partial differential equations and methods used to attack problems that do not have clean or simple solutions. Topics include techniques for solving partial differential equations exactly, the Fourier transform, perturbation theory, variational methods, Monte Carlo techniques, and finite difference schemes. PREREQUISITES: MATH 350

This course builds on CMSC/STAT 205, providing a deeper exploration of statistical computing in R. Topics might include efficient programming techniques, parallelization, statistical algorithms, advanced data visualization, and creation of R packages. Statistical software will be used extensively in this course. The class will be taught in an interactive lab-based format. There will be regular assignments and a project. PREREQUISITES: CMSC 205

Computer approximated (numerical) solutions to a variety of problems with an emphasis on error analysis. Interpolation, evaluation of polynomials and series, solution of linear and non-linear equations, eigenvectors, quadrature (integration), and differential equations. PREREQUISITES: MATH 250, one CMSC (computer science) course recommended

The study of local and global maximums and minimums of function, given various sorts of constraints. Linear problems and the simplex algorithm, general non-linear problems and the Kuhn-Tucker conditions, convex problems. Perturbation of problem parameters and duality. Applications to a wide variety of fields, including economics, game theory, and operations research. PREREQUISITES: MATH 230 and 250, or MATH 310

Development of the mathematical theory of statistics and its application to the real world. The course will focus on the principles of estimation and testing from both the frequentist and Bayesian perspectives. Resampling methods (permutation tests and bootstrap intervals) will also be explored. PREREQUISITES: MATH/STAT 340

Development of the mathematical theory of statistics and its application to the real world. The course will focus on the principles of estimation and testing from both the frequentist and Bayesian perspectives. Resampling methods (permutation tests and bootstrap intervals) will also be explored. PREREQUISITES: MATH/STAT 340

A study of the Bayesian statistical philosophy, contrasting it with the traditional frequentist approach taught in other statistics courses. Topics include Bayes' Theorem, prior and posterior probability distributions, hierarchical models, and Markov Chain Monte Carlo methods. The course will involve a mixture of lecture, discussion, and use of statistical software. Requirements include exams, a project, and assignments involving the use of statistical software. PREREQUISITES: MATH/STAT 340

This course expands on STAT 255, and introduces more sophisticated models, meant to capture complicated correlation structure in data. Topics might include generalized linear models, mixed-effects models, hierarchical models, spatial models, and time series. The course will involve the use of statistical software. There will be regular assignments, exams, and possibly projects. PREREQUISITES: STAT 255 or instructor permission

The study of groups, group actions, and important examples of finite and matrix groups. Specific topics will include group homomorphisms, quotient groups, isomorphism theorems, Lagrange's Theorem, the Orbit- Stabilizer Theorem, and the Sylow Theorems. PREREQUISITES: MATH 230 and MATH 250; or MATH 300 and consent of instructor

A study of concepts in mathematical analysis, including convergence of sequences and series, continuity, differentiation, integration, and metric spaces. PREREQUISITES: MATH 230 and MATH 250

A survey of graph theory that balances the abstract theory of graphs with a wide variety of algorithms and applications to “real world” problems. Topics include trees, Euler tours and Hamilton cycles, matchings, colorings, directed graphs, and networks. PREREQUISITES: MATH 230 and 250, or MATH 300

An introduction to functions of a complex variable, the Cauchy-Riemann equations, conformal mappings, Cauchy’s theorem, Cauchy’s integral formula, Taylor and Laurent series, and a sampling, as time and interest permit, of the corollaries to Cauchy’s theorem. PREREQUISITES: MATH 230 and 250

Modern algebra with topics selected from group theory, ring theory, field theory, classical geometric construction problems, and Galois theory. Emphasis on the use of mathematical abstraction to illuminate underlying relationships and structure. PREREQUISITES: MATH 230 and 250

Selected topics in analysis covering a wide variety of spaces and leading to applications of classical importance. In recent years, topics have included fixed point theory, inverse and implicit function theorems, abstract theory of differential equations, Lebesgue measure and integration, Fourier series and transforms.

A study of interconnections between abstract algebra (especially finite group theory) and combinatorics (especially graph theory). Topics will include classical results (such as the matrix-tree theorem), as well as recent subjects and advances (such as the abelian sandpile model and the Riemann-Roch theorem for graphs).

A study of metric and topological spaces, including continuity, compactness, connectedness, product and quotient spaces. Additional topics may include Zorn’s Lemma, separation properties, surfaces, the fundamental group, and fixed point theorems. PREREQUISITES: MATH 230 and 250

A study of the integers, including unique factorization, congruences, and quadratic reciprocity. Other topics may include finite fields, higher reciprocity laws, and algebraic number theory. PREREQUISITES: MATH 230 and 250

We study ideas developed by mathematicians whose work has historically been undervalued in mathematics, including Black and Indigenous mathematicians, and mathematicians of color. The first half of the course will focus on understanding the mathematics underlying current research of a prominent modern mathematician. For the other half of the course, students will explore and present research of mathematicians of interest to them. PREREQUISITES: Math 230, Math 250

Advanced work in mathematics on topics not covered in regular offerings. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Guided independent study of an advanced topic in undergraduate mathematics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

A study of the history of mathematics from the ancient Greeks through the present, emphasizing the role of mathematics in scientific advances, the work of great mathematicians, and the modern branching of the subject into a multitude of specialties. PREREQUISITES: MATH 310

Advanced work in mathematics on topics not covered in regular offerings. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Intended for students majoring in MATH or MAEC, who wish to complete a senior experience project in statistics. Students will work on a research project, applying skills learned throughout the statistics curriculum. Requirements include a written report and periodic oral presentations. A student must submit a written proposal, and have it approved by the instructor(s) prior to the start of the course. PREREQUISITES: For MATH majors: Senior standing and a project proposal approved by instructor(s) through one-unit indepenent study, and STAT 255, and MATH 340, and one 400-level STAT class, and one of CMSC 205, or CMSC 208. Either MATH 340 or the 400-level STAT class may be taken concurrently with STAT 698 . For MAEC majors: Senior standing and a project proposal approved by the instructor(s) through one-unit independent study, and STAT 255, and MATH 340, and ECON 380. MATH 340 may be taken concurrently with STAT 698.

Guided independent study of an advanced topic in undergraduate mathematics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.

Guided independent study of an advanced topic in undergraduate statistics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper. PREREQUISITES: To register student must complete the Student Initiated Course Form with consultation of supervising instructor.