Mathematics and Statistics
Mathematics is an art, a pure science, a language, and an analytical tool for the natural and social sciences, a means of exploring philosophical questions, and a beautiful edifice that is a tribute to human creativity. The mathematics curriculum is designed to provide essential skills for students in a variety of disciplines and to provide mathematics majors with a deep understanding of mathematics as it has evolved over the past two thousand years and how it is practiced today.
Statistics is the science of giving meaning to data in the context of uncertainty. Statisticians are involved in data collection and study design, data analysis, and the communication of information to a broad audience. The statistics curriculum is designed to balance both statistical theory and application, and will provide students the opportunity to work on real world data problems and enhance their communication skills.
Students who wish to major in both Mathematics and Statistics should note the College policy that double majors may count no more than four courses toward both majors. Courses for which a student earns AP Credit, such as calculus, are included among these four courses.
Mathematics Skills Center:
This Center offers extra assistance to students in lower-level mathematics courses and other courses requiring basic mathematical skills.
Requirements for the Mathematics Major
The Mathematics major requires 72 credits:
- A. Required Core Courses (take either Mathematics 101 or 111 and either Mathematics 210 or 211 and all of remaining courses listed):
- B. Electives (36 credits): Six courses from among:
- CS 252 Algorithms
- CS 254 Computability and Complexity
- CS 352 Advanced Algorithms (not offered in 2023-24)
- MATH 240 Probability
- MATH 241 Ordinary Differential Equations
- MATH 244 Geometries
- MATH 251 Chaotic Dynamics (not offered in 2023-24)
- MATH 261 Functions of a Complex Variable (not offered in 2023-24)
- MATH 271 Computational Mathematics
- MATH 282 Elementary Theory of Numbers
- MATH 295 Introduction to Computational Algebraic Geometry
- MATH 321 Real Analysis I
- MATH 331 Real Analysis II (not offered in 2023-24)
- MATH 332 Advanced Linear Algebra
- MATH 333 Combinatorial Theory (not offered in 2023-24)
- MATH 341 Partial Differential Equations
- MATH 342 Abstract Algebra I
- MATH 344 Differential Geometry (not offered in 2023-24)
- MATH 349 Methods of Teaching Mathematics
- MATH 352 Galois Theory
- MATH 354 Topology
- MATH 361 Complex Analysis
- MATH 362 Representation Theory of Finite Groups (not offered in 2023-24)
- MATH 395 Introduction to Analytic Number Theory (not offered in 2023-24)
- STAT 250 Introduction to Statistical Inference
- STAT 320 Time Series Analysis
- STAT 340 Bayesian Statistics (not offered in 2023-24)
At least four of these electives must be Carleton courses with a MATH designation. At least three of the following five areas of mathematics must be represented by the six electives (36 credits).
- Algebra:
- Analysis:
- Applied Mathematics:
- Discrete Structures:
- Geometry and Topology:
Of the six advanced courses, at least four must be Carleton courses with a Mathematics designation. Advanced courses substituted for Mathematics 232 or Mathematics 236 must also be Carleton courses with a Mathematics designation.
In addition, each senior major must complete an integrative exercise, Mathematics 400 (6 credits) which can be either a group or individual project. Majors must also accumulate eight talk credits during their junior and senior year by attending colloquia and the comps talks of their fellow mathematics or statistics majors. Students who major in both Mathematics and Statistics must accumulate a total of thirteen talk credits. We encourage majors to participate in the numerous activities that take place in the department.
Potential majors with especially strong preparation may petition the department for permission to substitute an advanced course for Mathematics 232 and/or for Mathematics 236. Advanced courses substituted for Mathematics 232 or Mathematics 236 must also be Carleton courses with a Mathematics designation.
There are many patterns of courses for the major depending upon a student's mathematical interests and career goals. A guide for majors, which supplies information about suitable patterns of courses, is available on the Mathematics and Statistics Department website.
Major under Combined Plan in Engineering:
In addition to completing requirements for the mathematics major listed above including Mathematics 241 and 341, the student should take the following courses required for admission to engineering schools: Two terms of 100-level Physics, Chemistry 123, 224, and Computer Science 111.
Requirements for the Statistics Major
The requirements for the Statistics Major are 74 credits:
- A. Supporting Courses (30 credits) Take either Mathematics 101 or 111 and either Mathematics 210 or 211 and all of remaining courses listed:
- B. Required Core (18 credits): All of the following, of which at least two must be taken at Carleton
- C. Electives (18 credits): Three electives, of which at least two must be Carleton courses with a Statistics designation
- CS 314 Data Visualization
- CS 320 Machine Learning
- CS 362 Computational Biology
- MATH 271 Computational Mathematics
- STAT 220 Introduction to Data Science
- STAT 260 Introduction to Sampling Techniques
- STAT 310 Spatial Statistics
- STAT 320 Time Series Analysis
- STAT 330 Advanced Statistical Modeling (not offered in 2023-24)
- STAT 340 Bayesian Statistics (not offered in 2023-24)
- D. Statistical Practice (2 credits):
-
- STAT 285 Statistical Consulting
In addition, each senior major must complete an integrative exercise. Statistics 400 (6 credits), which can be either a group or individual project. Majors must accumulate eight talk credits during their junior and senior year by attending department colloquia and the comps talks of their fellow mathematics or statistics majors. Students who major in both Mathematics and Statistics must accumulate a total of thirteen talk credits. We encourage majors to participate in the numerous activities that take place in the department.
We recommend statistics majors also take courses in a discipline in which statistics can be applied. Students interested in data science should consider taking additional computer science courses.
Students considering graduate school in statistics or biostatistics are strongly encouraged to take Mathematics 236 (Mathematical Structures) and Mathematics 321 (Real Analysis). Consult a statistics faculty member for more information specific to your choice of program.
Requirements for the Mathematics Minor
To earn a minor in Mathematics, a student must earn 42 credits from courses taken in the Department of Mathematics and Statistics at Carleton. (Students who place out of courses based on work done outside of Carleton are still required to earn 42 credits from courses taken in the Department of Mathematics and Statistics at Carleton.) At least 36 of the required 42 credits must come from courses with a Mathematics designation. In addition, the only Statistics courses which can be counted toward the Mathematics minor are Statistics 250, 320 and 340.
Students who wish to major in Statistics and minor in Mathematics should note the College policy that a student may not fulfill more than half the credits for a minor from the courses counted toward their major or majors.
Mathematics Courses
MATH 101 Calculus with Problem Solving An introduction to the central ideas of calculus with review and practice of those skills needed for the continued study of calculus. Problem solving strategies will be emphasized. In addition to regular MWF class time, students will be expected to attend two problem-solving sessions each week, one on Monday or Tuesday, and one on Wednesday or Thursday. Details will be provided on the first day of class. Prerequisite: Not open to students who have received credit for Mathematics 111. 6 credits; FSR; Fall, Winter; Deanna B Haunsperger
MATH 111 Introduction to Calculus An introduction to the differential and integral calculus. Derivatives, antiderivatives, the definite integral, applications, and the fundamental theorem of calculus. Prerequisite: Requires placement via the Calculus Placement Exam 1, see Mathematics web page. Not open to students who have received credit for Mathematics 101. 6 credits; FSR; Fall, Winter, Spring; Rebecca Terry, Joseph D Johnson, Rob C Thompson, Corey Brooke
MATH 120 Calculus 2 Inverse functions, integration by parts, improper integrals, modeling with differential equations, vectors, calculus of functions of two independent variables including directional derivatives and double integrals, Lagrange multipliers. Prerequisite: Mathematics 101, 111, score of 4 or 5 on Calculus AB Exam or placement via a Carleton placement exam. Not open to students who have received credit for Mathematics 211 or have a score of 4 or 5 on the AP Calculus BC exam. 6 credits; FSR; Fall, Winter, Spring; Claudio Gómez-Gonzáles, Corey Brooke, Sunrose T Shrestha
MATH 206 A Tour of Mathematics A series of eight lectures intended for students considering a Mathematics major. The emphasis will be on presenting various striking ideas, concepts and results in modern mathematics, rather than on developing extensive knowledge or techniques in any particular subject area. 1 credit; S/CR/NC; NE; Winter; Claudio Gómez-Gonzáles
MATH 210 Calculus 3 Vectors, curves, calculus of functions of three independent variables, including directional derivatives and triple integrals, cylindrical and spherical coordinates, line integrals, Green's theorem, sequences and series, power series, Taylor series. Prerequisite: Mathematics 120. This course cannot be substituted for Mathematics 211. 6 credits; FSR; Winter, Spring; Corey Brooke, Caroline L Turnage-Butterbaugh
MATH 211 Introduction to Multivariable Calculus Vectors, curves, partial derivatives, gradient, multiple and iterated integrals, line integrals, Green's theorem. Prerequisite: Score of 4 or 5 on the AP Calculus BC exam, or placement via Calculus Placement Exam #3. 6 credits; FSR; Fall, Winter; Rebecca Terry, Josh R Davis, Mike Adams
MATH 232 Linear Algebra Linear algebra centers on the study of highly structured functions called linear transformations. Given the abundance of nonlinear functions in mathematics, it may come as a surprise that restricting to linear ones opens the door to a rich and powerful theory that finds applications throughout mathematics, statistics, computer science, and the natural and social sciences. Linear transformations are everywhere, once we know what to look for. They appear in calculus as the functions that are used to define lines and planes in Euclidean space. In fact, differentiation is also a linear transformation that takes one function to another. The course focuses on developing geometric intuition as well as computational matrix methods. Topics include kernel and image of a linear transformation, vector spaces, determinants, eigenvectors and eigenvalues. Prerequisite: Mathematics 120 or Mathematics 211. 6 credits; FSR; Fall, Winter, Spring; Rafe F Jones, Mike Adams, Rebecca Terry
MATH 236 Mathematical Structures Basic concepts and techniques used throughout mathematics. Topics include logic, mathematical induction and other methods of proof, problem solving, sets, cardinality, equivalence relations, functions and relations, and the axiom of choice. Other topics may include: algebraic structures, graph theory, and basic combinatorics. Prerequisite: Mathematics 232 and either Mathematics 210 or Mathematics 211. 6 credits; FSR; Fall, Winter, Spring; Caroline L Turnage-Butterbaugh, Claudio Gómez-Gonzáles, Deanna B Haunsperger
MATH 240 Probability Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions. Prerequisite: Mathematics 120 or Mathematics 211. 6 credits; FSR; Fall, Winter; Adam Loy, Katie R St. Clair
MATH 241 Ordinary Differential Equations Ordinary differential equations are a fundamental language used by mathematicians, scientists, and engineers to describe processes involving continuous change. In this course we develop ordinary differential equations as models of real world phenomena and explore the mathematical ideas that arise within these models. Topics include separation of variables; phase portraits; equilibria and their stability; non-dimensionalization; bifurcation analysis; and modeling of physical, biological, chemical, and social processes. Prerequisite: Mathematics 232 or instructor permission. 6 credits; FSR; Winter, Spring; Joseph D Johnson, Rob C Thompson
MATH 244 Geometries Euclidean geometry from an advanced perspective; projective, hyperbolic, inversive, and/or other geometries. Recommended for prospective secondary school teachers. Prerequisite: Mathematics 236. 6 credits; FSR; Fall; Sunrose T Shrestha
MATH 251 Chaotic Dynamics An exploration of the behavior of non-linear dynamical systems. Topics include one and two-dimensional dynamics, Sarkovskii's Theorem, chaos, symbolic dynamics, and the Hénon Map. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Not offered 2023-24
MATH 261 Functions of a Complex Variable Algebra and geometry of complex numbers, analytic functions, complex integration, series, residues, applications. Not open to students who have already received credits for Mathematics 361. Prerequisite: Mathematics 210 or Mathematics 211. 6 credits; FSR; Not offered 2023-24
MATH 271 Computational Mathematics An introduction to mathematical ideas from numerical approximation, scientific computing, and/or data analysis. Topics will be selected from numerical linear algebra, numerical analysis, and optimization. Theory, implementation, and application of computational methods will be emphasized. Prerequisite: Mathematics 232. 6 credits; FSR; Winter; Rob C Thompson
MATH 282 Elementary Theory of Numbers A first course in number theory, covering properties of the integers. Topics include the Euclidean algorithm, prime factorization, Diophantine equations, congruences, divisibility, Euler’s phi function and other multiplicative functions, primitive roots, and quadratic reciprocity. Along the way we will encounter and explore several famous unsolved problems in number theory. If time permits, we may discuss further topics, including integers as sums of squares, continued fractions, distribution of primes, Mersenne primes, the RSA cryptosystem. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Winter; Rafe F Jones
MATH 295 Introduction to Computational Algebraic Geometry Classical algebraic geometry is the study of geometric objects defined by polynomial equations. This course will cover fundamental concepts and techniques—varieties, ideals, and Gröbner bases, to name a few—as well as algorithms for solving equations and computing intersections of curves and surfaces. Ultimately, this course will build towards several beautiful results: the 27 lines on a cubic surface, the 28 bitangents on a planar quartic, and the construction of regular polygons. Students will learn to use software such as SageMath to perform computations and practice visualization. While familiarity with Python would be helpful, it is by no means required! Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Spring; Claudio Gómez-Gonzáles
MATH 297 Assessment and Communication of External Mathematical Activity An independent study course intended for students who have completed an external activity related to the mathematics major (for example, an internship or an externship) to communicate (both in written and oral forms) and assess their mathematical learning from that activity. Prerequisite: Permission of department chair and homework in advance of the external mathematical activity. 1 credit; S/CR/NC; NE; Fall, Winter, Spring; Rafe F Jones
MATH 321 Real Analysis I A systematic study of concepts basic to calculus, such as topology of the real numbers, limits, differentiation, integration, convergence of sequences, and series of functions. Prerequisite: math.236 or math.236p. 6 credits; FSR; Fall, Spring; Caroline L Turnage-Butterbaugh, Sunrose T Shrestha
MATH 331 Real Analysis II Further topics in analysis such as measure theory, Lebesgue integration or Banach and Hilbert spaces. Prerequisite: Mathematics 321 or instructor permission. 6 credits; FSR; Not offered 2023-24
MATH 332 Advanced Linear Algebra Selected topics beyond the material of Mathematics 232. Topics may include the Cayley-Hamilton theorem, the spectral theorem, factorizations, canonical forms, determinant functions, estimation of eigenvalues, inner product spaces, dual vector spaces, unitary and Hermitian matrices, operators, infinite-dimensional spaces, and various applications. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Fall; Rob C Thompson
MATH 333 Combinatorial Theory The study of structures involving finite sets. Counting techniques, including generating functions, recurrence relations, and the inclusion-exclusion principle; existence criteria, including Ramsey's theorem and the pigeonhole principle. Some combinatorial identities and bijective proofs. Other topics may include graph and/or network theory, Hall's ("marriage") theorem, partitions, and hypergeometric series. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Not offered 2023-24
MATH 341 Partial Differential Equations An introduction to partial differential equations with emphasis on the heat equation, wave equation, and Laplace's equation. Topics include the method of characteristics, separation of variables, Fourier series, Fourier transforms and existence/uniqueness of solutions. Prerequisite: Mathematics 241. 6 credits; FSR; Spring; Joseph D Johnson
MATH 342 Abstract Algebra I Introduction to algebraic structures, including groups, rings, and fields. Homomorphisms and quotient structures, polynomials, unique factorization. Other topics may include applications such as Burnside's counting theorem, symmetry groups, polynomial equations, or geometric constructions. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Winter; Claudio Gómez-Gonzáles
MATH 344 Differential Geometry Local and global theory of curves, Frenet formulas. Local theory of surfaces, normal curvature, geodesics, Gaussian and mean curvatures, Theorema Egregium. Prerequisite: Mathematics 236 or permission of the instructor. 6 credits; FSR; Not offered 2023-24
MATH 349 Methods of Teaching Mathematics Methods of teaching mathematics in grades 7-12. Issues in contemporary mathematics education. Regular visits to school classrooms and teaching a class are required. Prerequisite: Junior or senior standing and instructor permission. 6 credits; NE; Fall; Deanna B Haunsperger
MATH 352 Galois Theory In the nineteenth century, Évariste Galois discovered a deep connection between field theory and group theory. Now known as Galois theory, this led to the resolution of several centuries-old problems, including whether there is a version of the quadratic formula for higher-degree polynomials, and whether the circle can be squared. Today Galois theory is a fundamental concept for many mathematical fields, from topology to algebra to number theory. This course develops the theory in a modern framework, and explores several applications. Topics include field extensions, classical constructions, splitting fields, the Galois correspondence, Galois groups of polynomials, and solvability by radicals. Prerequisite: Mathematics 342. 6 credits; FSR; Spring; Rafe F Jones
MATH 354 Topology An introduction to the study of topological spaces. We develop concepts from point-set and algebraic topology in order to distinguish between different topological spaces up to homeomorphism. Topics include methods of construction of topological spaces; continuity, connectedness, compactness, Hausdorff condition; fundamental group, homotopy of maps. Prerequisite: Mathematics 236 or instructor permission. 6 credits; FSR; Winter; Josh R Davis
MATH 361 Complex Analysis The theoretical foundations for the calculus of functions of a complex variable. Prerequisite: Mathematics 321 or instructor permission. Students who have already received credit for Mathematics 261 may only take this course with instructor permission. 6 credits; FSR; Winter; Caroline L Turnage-Butterbaugh
MATH 362 Representation Theory of Finite Groups Representation theory is the study of mathematical structures via the tools of linear algebra. The first objects to be studied in this way were finite groups at the end of the nineteenth century, motivated by the powerful framework of characters in number theory, but the field has generalized incredibly due to the prevalence of symmetry throughout mathematics, physics, and beyond. In this course the focus is on finite groups. Topics include Maschke’s theorem, complete reducibility, and Schur’s lemma; characters, orthogonality relations, and character tables; Fourier transformations and random walks. Additional topics may include Burnside’s Lemma, Frobenius reciprocity, and an exploration of representations of infinite groups. Prerequisite: Mathematics 342. 6 credits; Not offered 2023-24
MATH 395 Introduction to Analytic Number Theory An introduction to the techniques and principles of analytic number theory. Topics covered include arithmetical functions, Dirichlet multiplication, averages of arithmetical functions, elementary theorems on the distribution of the primes, and Dirichlet's theorem on primes in arithmetic progressions. Prerequisite: Math 321 (or instructor permission) and Math 342. 6 credits; FSR; Not offered 2023-24
MATH 399 Senior Seminar As part of their senior capstone experience, majors will work together in teams (typically three to four students per team) to develop advanced knowledge in a faculty-specified area or application of mathematics, and to design and implement the first stage of a project completed the following term. Prerequisite: Open only to senior Math majors. 6 credits; S/CR/NC; NE; Fall; Rob C Thompson
MATH 400 Integrative Exercise Either a supervised small-group research project or an individual, independent reading. Required of all senior majors. Prerequisite: Mathematics 236 and successful completion of three courses from among: Mathematics courses numbered above 236, Computer Science 252, Computer Science 254, Computer Science 352, Statistics 250, Statistics 320, Statistics 340. 3 credits; S/NC; Fall, Winter, Spring; Deanna B Haunsperger, Caroline L Turnage-Butterbaugh, Rafe F Jones, Rob C Thompson, Sunrose T Shrestha
Statistics Courses
STAT 120 Introduction to Statistics Introduction to statistics and data analysis. Practical aspects of statistics, including extensive use of the statistical software R, interpretation and communication of results, will be emphasized. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, basic probability, the normal distribution, randomization approach to inference, sampling distributions, estimation, hypothesis testing, and two-way tables. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 240/Statistics 250 Probability/Statistical Inference sequence. Prerequisite: Not open to students who have already received credit for Psychology 200/201, Sociology/Anthropology 239 or Statistics 250. 6 credits; FSR, QRE; Fall, Winter, Spring; Deepak Bastola, Andy N Poppick, Claire E Kelling, Katie R St. Clair, Adam Loy
STAT 220 Introduction to Data Science This course will cover the computational side of data analysis, including data acquisition, management, and visualization tools. Topics may include: data scraping, data wrangling, data visualization using packages such as ggplots, interactive graphics using tools such as Shiny, supervised and unsupervised classification methods, and understanding and visualizing spatial data. We will use the statistics software R in this course. Prerequisite: Statistics 120, Statistics 230 or Statistics 250. 6 credits; FSR, QRE; Fall, Winter, Spring; Claire E Kelling, Deepak Bastola
STAT 230 Applied Regression Analysis A second course in statistics covering simple linear regression, multiple regression and ANOVA, and logistic regression. Exploratory graphical methods, model building and model checking techniques will be emphasized with extensive use of statistical software to analyze real-life data. Prerequisite: Statistics 120, Statistics 250, Psychology 200, or AP Statistics Exam score of 4 or 5. 6 credits; FSR, QRE; Fall, Winter, Spring; Claire E Kelling, Adam Loy, Andy N Poppick
STAT 250 Introduction to Statistical Inference Introduction to modern mathematical statistics. The mathematics underlying fundamental statistical concepts will be covered as well as applications of these ideas to real-life data. Topics include: resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodness-of-fit tests, regression, and Bayesian methods. The statistical package R will be used to analyze data sets. Prerequisite: Mathematics 240 Probability. 6 credits; FSR, QRE; Winter, Spring; Andy N Poppick, Katie R St. Clair
STAT 260 Introduction to Sampling Techniques Covers sampling design issues beyond the basic simple random sample: stratification, clustering, domains, and complex designs like two-phase and multistage designs. Inference and estimation techniques for most of these designs will be covered and the idea of sampling weights for a survey will be introduced. We may also cover topics like graphing complex survey data and exploring relationships in complex survey data using regression and chi-square tests. Prerequisite: Statistics 120, Statistics 230, or Statistics 250. 6 credits; FSR, QRE; Winter; Katie R St. Clair
STAT 285 Statistical Consulting Students will apply their statistical knowledge by analyzing data problems solicited from the Northfield community. Students will also learn basic consulting skills, including communication and ethics. Prerequisite: Statistics 230 and instructor permission. 2 credits; S/CR/NC; FSR, QRE; Fall, Winter, Spring; Adam Loy
STAT 297 Assessment and Communication of External Statistical Activity An independent study course intended for students who have completed an external activity related to the statistics major (for example, an internship or an externship) to communicate (both in written and oral forms) and assess their statistical learning from that activity. Prerequisite: Permission of department chair and homework in advance of the external statistical activity. 1 credit; S/CR/NC; Fall, Winter, Spring; Rafe F Jones
STAT 310 Spatial Statistics Spatial data is becoming increasingly available in a wide range of disciplines, including social sciences such as political science and criminology, as well as natural sciences such as geosciences and ecology. This course will introduce methods for exploring and analyzing spatial data. Methods will be covered to describe and analyze three main types of spatial data: areal, point process, and point-referenced (geostatistical) data. The course will also extensively cover tools for working with spatial data in R. The goals are that by the end of the course, students will be able to read, explore, plot, and describe spatial data in R, determine appropriate methods for analyzing a given spatial dataset, and work with their own spatial dataset(s) in R and derive conclusions about an application through statistical inference. Prerequisite: Statistics 230 and Statistics 250. 6 credits; FSR, QRE; Spring; Claire E Kelling
STAT 320 Time Series Analysis Models and methods for characterizing dependence in data that are ordered in time. Emphasis on univariate, quantitative data observed over evenly spaced intervals. Topics include perspectives from both the time domain (e.g., autoregressive and moving average models, and their extensions) and the frequency domain (e.g., periodogram smoothing and parametric models for the spectral density). Prerequisite: Statistics 230 and 250. Exposure to matrix algebra may be helpful but is not required. 6 credits; FSR, QRE; Fall; Andy N Poppick
STAT 330 Advanced Statistical Modeling Topics include linear mixed effects models for repeated measures, longitudinal or hierarchical data and generalized linear models (of which logistic and Poisson regression are special cases) including zero-inflated Poisson models. Depending on time, additional topics could include survival analysis, generalized additive models or models for spatial data. Prerequisite: Statistics 230 and 250 or permission of the instructor. 6 credits; FSR, QRE; Not offered 2023-24
STAT 340 Bayesian Statistics An introduction to statistical inference and modeling in the Bayesian paradigm. Topics include Bayes’ Theorem, common prior and posterior distributions, hierarchical models, Markov chain Monte Carlo methods (e.g., the Metropolis-Hastings algorithm and Gibbs sampler) and model adequacy and posterior predictive checks. The course uses R extensively for simulations. Prerequisite: Statistics 250. 6 credits; FSR, QRE; Not offered 2023-24
STAT 399 Senior Seminar As part of their senior capstone experience, majors will work together in teams (typically three to four students per team) to develop advanced knowledge in a faculty-specified area or application of statistics, and to design and implement the first stage of a project completed the following term. Prerequisite: Senior standing and instructor permission. Students are required to take Statistics 230 and Statistics 250 before enrolling. 6 credits; NE; Winter; Andy N Poppick
STAT 400 Integrative Exercise Either a supervised small-group research project or an individual, independent reading. Required of all senior majors. Prerequisite: Senior Statistics major. Students are strongly encouraged to complete Statistics 230 and Statistics 250 before starting this course. 3 credits; S/NC; Fall, Winter, Spring; Deanna B Haunsperger, Claire E Kelling, Andy N Poppick, Adam Loy