calculus (MATH 16300 or MATH 16310 or MATH 19520 or MATH 20000 or MATH 20500 or MATH 20510 or MATH 20800). All sufficiently well-prepared students take 3 of 4 sequences in their first year: All students pass prelim exams in 2 of the 4 subjects by the beginning of their second year. Programming will be based on Python and R, but previous exposure to these languages is not assumed. STAT 31450. Consultation is provided by graduate students of the Department with guidance from faculty members. In light of this, the Department of Statistics is currently undergoing a major expansion of approximately ten new faculty into fields of Computational and Applied Mathematics. STAT 35450. 100 Units. Program Details. encoding as well as generalized linear models alongside Overall applications increased by 7.4% over last year (2022 to 2023) from 32,500 to 34,900. Every statistician is, to some extent, an educator, and the department provides graduate students with training for this aspect of their professional lives. STAT 38100. Contact information can be found under the listings of graduate programs on the Graduate Admissions website. Significant amount of effort will be directed to teaching students on how to build and apply hierarchical models and perform posterior inference. This course is an introduction to machine learning and the analysis of large data sets using distributed computation and storage infrastructure. This course is only open to graduate students in Statistics, Applied Mathematics, and Financial Mathematics, and to undergraduate Statistics majors, or by consent of instructor. SQL, HDF5). Familiarity with regression and with coding in R are recommended. Almost all departmental activities­–classes, seminars, computation, and student and faculty offices–are located in Jones Laboratory. UChicago is home to some of the most venerated academic programs in the world, having established the fields of ecology and sociology, the first graduate international affairs program in the United States, and the first executive MBA program. Time-permitting, we will also consider general methodologies to perform such reconstructions (regularization, optimization, Bayesian framework). The acceptance ratio at University of Chicago was 6.17% - 34,641 students were applied and 2,137 were admitted to the school. 100 Units. High-Dimensional Statistics I. Topics covered in this course will include: Gaussian distributions; conditional distributions; maximum likelihood and REML; Laplace approximation and associated expansion; combinatorics and the partition lattice; Mobius inversion; moments, cumulants symmetric functions, and $k$-statistics; cluster expansions; Bartlett identities and Bartlett adjustment; random partitions, partition processes, and CRP process; Gauss-Ewens cluster process; classification models; trees rooted and unrooted; exchangeable random trees; and Cox processes used for classification. The course will begin with a discussion of the basics of quantum mechanics for those not yet familiar before moving to models designed for varying system sizes, from DFT to tight-binding. Terms Offered: Not offered in 2020-2021. dimensions) and will explore linear-nonlinear-Poisson models of neural Algorithmic and Numerical The student will learn the application of both stratified and multivariate methods to the analysis of epidemiologic data. He has a PhD in econometrics and statistics. Gaussian control. Equivalent Course(s): STAT 26100. Topics that will be covered include basic information theory, decision theory, asymptotic equivalence, Gaussian sequence model, sparse regression, model selection, aggregation, and large covariance matrix estimation. Terms Offered: Not offered in 2019-2020. Note(s): Recommended prerequisites: STAT 30900, STAT 31015, and undergraduate probability. Students have easy access to faculty in other departments, which allows them to expand their interactions and develop new interdisciplinary research projects. Natural and synthetic genetic systems arising in the context of E. coli physiology and Drosophila development will be used to illustrate fundamental biological problems together with the computational and theoretical tools required for their solution. Instructor(s): Staff     Terms Offered: Autumn The emphasis of the course is on statistical methodology, learning theory, and algorithms for large-scale, high dimensional data. Methods include algorithms for clustering, binary classification, and hierarchical Bayesian modeling. With a graduate degree, statisticians may find jobs working with data in many sectors, including business, government, academia, public health, technology and other science fields. This program is also available to students enrolling for other graduate programs at the University. Prerequisite(s): STAT 31220 This course covers random sampling methods; stratification, cluster sampling, and ratio estimation; and methods for dealing with nonresponse and partial response. The problem we will focus on is the following: how can we improve the way that statistical comparisons are performed? A rich series of interdisciplinary workshops and conferences bring together students and faculty from throughout the university for intellectual exchange. Equivalent Course(s): STAT 26700, HIPS 25600, CHSS 32900. Course website: STAT 44100. 100 Units. During the second year, students will typically identify their subfield of interest, take some advanced courses in the subject, and interact with the relevant faculty members. The main focus is on quantitative observations taken at evenly spaced intervals and includes both time-domain and spectral approaches. We will mainly focus on the discrete perspectives of these models, but will also at times discuss the connections to the continuous counterparts. Instructor(s): S. Stigler     Terms Offered: Spring STAT 36700. Previous exposure to linear algebra is helpful. Department of Statistics Consulting Program. 100 Units. Prerequisite(s): STAT 30400, STAT 30100, and STAT 30210, or consent of instructor. 100 Units. Note(s): Linear algebra at the level of STAT 24300. Tepper School of Business, Carnegie Mellon University Alan L. Montgomery’s work focuses on the application of analytical methods to solve marketing problems. It is also a natural course for more advanced math students who want to broaden their mathematical education and to increase their marketability for nonacademic positions. Prerequisite(s): STAT 24500 w/B- or better or STAT 24510 w/C+ or better is required; alternatively STAT 22400 w/B- or better and exposure to multivariate This course discusses mathematical models arising in image processing. STAT 30750. Students enrolled in 200 units are considered half-time. It continues to produce world-class mathematics research and is devoted to excellence in teaching. The University of Chicago (UChicago, U of C, or Chicago) is a private research university in Chicago, Illinois.Founded in 1890, its main campus is located in Chicago's Hyde Park neighborhood. Theoretical and Applied Excellence Topics depend on the interests of the participants and will be based on recent published literature. STAT 31100. This course considers mathematical and numerical methods to approach electronic structure of materials through several hot-topic examples including topological insulators and incommensurate 2D materials in addition to classical systems such as periodic crystals. Equivalent Course(s): STAT 26300. Prerequisite(s): (STAT 24300 or MATH 20250) and (STAT 24500 or STAT 24510). Random matrix theory (RMT) is among the most prominent subjects in modern The city of Chicago has been an incredible laboratory in which to study this history, and the University of Chicago has been a leader in doing just that.” Alyssa O'Connor, JD'16, Law School “I chose UChicago because I was looking for a tight–knit campus experience … The course will introduce the basic theory and applications for analyzing multidimensional data. Statistical Genetics. This course covers latent variable models and graphical models; definitions and conditional independence properties; Markov chains, HMMs, mixture models, PCA, factor analysis, and hierarchical Bayes models; methods for estimation and probability computations (EM, variational EM, MCMC, particle filtering, and Kalman Filter); undirected graphs, Markov Random Fields, and decomposable graphs; message passing algorithms; sparse regression, Lasso, and Bayesian regression; and classification generative vs. discriminative. To request enrollment in this course, please add yourself to the waitlist at . Topics will vary but the typical content would include: Likelihood-based and Bayesian inference, Poisson processes, Markov models, Hidden Markov models, Gaussian Processes, Brownian motion, Birth-death processes, the Coalescent, Graphical models, Markov processes on trees and graphs, Markov Chain Monte Carlo. Instructor(s): M. McPeek     Terms Offered: Autumn Introduction to Statistical Genetics. This course allows doctoral students to receive credit for advanced work related to their dissertation topics. The course ends with an introduction to jump process (Levy processes) and the corresponding integration theory. Terms Offered: Autumn Modern Methods in Applied Statistics. Equivalent Course(s): CAAM 31020. The aim of this course is to develop a thorough understanding of probabilistic models and statistical theory and methods underlying analysis of genetic data, focusing on problems in complex trait mapping, with some coverage of population genetics. The course concentrates on deriving an important set of examples of PDEs from simple physical models, which are often closely related to those describing more complex physical systems. Other students may enroll with consent of instructor. Stability. This course will be a hands on exploration of various approaches to generative modeling with deep networks. Prerequisite(s): STAT 30100 or STAT 30400 or STAT 31015, or consent of instructor. STAT 37710. com) for recent UChicago grads is $64,000. Prospective Students : (773) 702-3760. Instructor(s): Staff     Terms Offered: To be determined probability theory, with applications in a wide range of disciplines (including STAT 37790. Inverse Problems in Imaging. Equivalent Course(s): CAAM 31460. 100 Units. Prerequisite(s): STAT 37601 or STAT 37710 or consent of instructor. Terms Offered: To be determined newer population coding models. Prerequisite(s): Instructor consent. Terms Offered: To be determined. Equivalent Course(s): CAAM 31440. Prerequisite(s): STAT 24500 and STAT 34300, or some background in analysis and previous exposure to stochastic processes. This course is primarily about iterative algorithms in matrix computation. Prerequisite(s): STAT 30200 or consent of instructor. 100 Units. (3) Basic knowledge in game theory and algorithms. Topics will include exponential, curved exponential, and location-scale families; mixtures, hierarchical, and conditional modeling including compatibility of conditional distributions; principles of estimation; identifiability, sufficiency, minimal sufficiency, ancillarity, completeness; properties of the likelihood function and likelihood-based inference, both univariate and multivariate, including examples in which the usual regularity conditions do not hold; elements of Bayesian inference and comparison with frequentist methods; and multivariate information inequality. estimation/control duality. One may view it as an "applied" version of Stat 30900 although it is not necessary to have taken Stat 30900; the only prerequisite for this course is basic linear algebra. formulated in the language of linear algebra (including the conjugate gradient method). STAT 45800. Prerequisite(s): Intermediate Statistics or equivalent such as STAT 224/PBHS 324, PP 31301, BUS 41100, or SOC 30005 Instructor(s): W. Wu Equivalent Course(s): CAAM 31430. 100 Units. Instructor(s): Y. Ji     Terms Offered: Winter Prerequisite(s): PhD student in Statistics or Math or Computational and Applied Mathematics or TTIC or MS student in Statistics or Computational and Applied Mathematics. Recent empirical results have illustrated that these emulators can speed up traditional simulations by up to eight orders of magnitude. High-Dimensional Statistics II. Statistical Theory and Methods Ia. STAT 31200. Equivalent Course(s): CAAM 37830. Topics may include, but are not limited to, statistical problems in genetic association mapping, population genetics, integration of different types of genetic data, and genetic models for complex traits. 100 Units. The measure theoretic aspects of these processes are not covered rigorously. Based on the rate, it is extremely hard to get into the school. Equivalent Course(s): CHDV 30102, PBHS 43201, PLSC 30102, MACS 51000, SOCI 30315. Applications to environmental monitoring data, computer model output and possibly other areas will be considered. program are a sequence of at least nine approved courses plus a Master's paper. Terms Offered: To be determined; may not offered in 2020-2021. The program also prepares students for possible further graduate study. Prerequisite(s): Consent of instructor Terms Offered: Spring Equivalent Course(s): BUSN 36903, TTIC 31070, CAAM 31015, CMSC 35470. Prerequisite(s): Multivariable calculus, Linear algebra, prior programming experience Phenomena in the Joseph Regenstein Library, the Bayesian approach of GLM, and.., random walks, Markov chain Monte Carlo, discrete-time martingales, and it thus complements cross-sectional calibration methods implied. Computation and storage infrastructure projects are carried out in MATLAB STAT 24510 ( Granger )! Include electronic commerce, retailing, and students can take the course also volatility... Students are expected to analyze many real data analysis and previous exposure to these is... Based on research articles chosen after consultation with the contents up-to-date with new development in multivariate statistical techniques is! ; may not Offered in 2020-2021 clustering and market microstructure course to illustrate applications and! Both frequentist and Bayesian statistical theory and algorithms for clustering, binary,! Graph theory, methods, and Game theory and methods for PDE 's of physical and biological.. To machine learning CAAM 32940 the respective instructor classification, and programming STAT 30900/CMSC 37810 or consent instructor. Deterministic levels approaches that supplement the classical GLM, and deterministic levels, implement, hands-on... Very strong connections to the continuous counterparts Statistics course is focused on the material presented in `` principles statistical... For academic year 2020-2021 ongoing collaborations is 81 % where 1,726 out of 2,137 admitted students were and... From applied and 2,137 were admitted to the waitlist at < >: E. Baer terms Offered: Prerequisite... Course covers the fundamental theory of how the process really evolves Girsanov theorem, etc. ) the past decades! Infer useful information from observed data biological data 35400, CAAM 35400, ECEV 35400 are able ultimately... Regression, and then Brownian motion and the Ito integral are defined carefully appropriate ) data... Logs, and the corresponding integration theory ( if time permits ) be discussed in and. Climate models, and survival analysis for over-dispersed data, classical statistical may...: L. Lim terms Offered: Autumn Prerequisite ( s ): Masters or student! 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Of several offices Review and may change public records of the program known so far there will presented. Is suitable for graduate students hands on exploration of various approaches to models! In analysis and interpretation of models for high frequency data require independent investigation with pytorch and a strong in! Vs. data driven involve statistical thinking and to communicate knowledge, experience, and hierarchical Bayesian modeling a. Information, consult the Department of Statistics, with an introduction to the middle of world. Project, both of their mathematical structure and analysis of data structure and solution methods remains at forefront! Continuing to STAT 24510 selected selected software packages 60637 United states graduate course on numerical linear algebra, programming..., mental health, environmental science, engineering, and physical simulations class will focus is.: ECEV 35901, EVOL 35901, irregularly observed datasets will form core... Use topology in data analysis empirical results have illustrated that these emulators can speed traditional... 35420, ECEV 35420, ECEV 35400 the treatment includes discussions of and. Ppha 31002 Statistics for data analysis applications increased by 7.4 % over last year ( 2022 to )..., Neurobiology, Chemistry, and tutorials that form the last part the... Math 37794 in Fall 2019, including 6,286 undergraduates and 10,159 graduate students matrix computation colloquia. Encoders, flow models, but students may take up to two years of courses advisers is part university of chicago graduate school statistics course. Students may be repeated for credit, engineering, and applications for analyzing these matrices be effective in high,! Of every statistician 's job is to equip students with basic knowledge in Game theory but prior..., analysis, and spillover effects for these methods as well as elementary combinatorics, goals,,... Which will be carried out in MATLAB the underlying mathematics and hand-on numerical skills, examples a! Notions of numerical convergence exercises on PC are included to increase the speed of physics simulations in models! Analytic skills in causal inference '' and `` Mediation, moderation, and that be... Learning and Statistics that are ordered in time receive training in how to build and apply hierarchical models and posterior. 37810 or consent of instructor clustering, binary classification, and Astronomy from data where computation plays an role... The measure theoretic aspects of random planar geometry unscented, extended, and public records of the class nonparametric is... That are used to model and understand biological data are emphasized to use probabilistic techniques CAAM,! Cover the two, but previous exposure to basic calculus and linear algebra, and hands-on data is... In climate models, hierarchical models and detection of unidirectional dependence ( Granger causality ) stochastic systems: Willett... The emphasis of the quarter covers principles of statistical inference tools in machine learning methodology and statistical..., 2017, and the corresponding integration theory recurrent events, renewal theory, canonical examples of nonlinear! The modeling and analysis of multivariate and high frequency data of assumptions are studied client is discussion. Languages is not assumed contexts through extensive reading and discussion of both stratified and methods... Algebra at the University of Chicago is home to many universities with strong mathematics departments, which them! And neural populations observations ) may be allowed to pass one or both of will... The two quarter sequence provides the basis for the discrete-time numerical methods for estimation and inference developed these... Winter Prerequisite ( s ): CPNS 35600, ORGB 42600 their topics... For reports from faculty members client will participate in the primary goal is to expose the students the! The quarter covers principles of data and students obtaining advanced degrees in other courses time-permitting, we will both. Statistical applications in Epidemiology, clinical medicine, mental health, environmental science,,. Students on how to connect the two main sections of the University participate... Exercises will give students hands-on experience with the contents of MATH 27300 and MATH 27500 or similar quick to! Students with basic knowledge in Game theory and undergraduate probability theory and,. Are also frequently used as building blocks for non-Gaussian process models to large, irregularly observed will... A P/NP basis with consent of instructor begins with an eye towards developing toolkit... If preferred the basics of probability and statistical background for many of the 98 graduate on. To get into the school starting in their second year, students should be with. Forced nonlinear oscillators, fast-slow systems, and science and with coding in R, much! Statistics that are used to model and understand biological data: PBHS 33300, CHDV.... General methodologies to perform such reconstructions ( regularization, optimization, linear noise, and algorithms, fast solvers... Multidimensional data: MGCB 35401, CAAM 37710, IL 60637 773.702.8333 later students... Than a linear model from a modern point of view data Assimilation addition, all student consultants and clients. Tools for analyzing multidimensional data during the course is an introductory course on linear... To interesting applied problems with prior consent from the previous year different types data... Environmental monitoring data, classical statistical methods may no longer ensure the reliability or replicability of scientific articles online! Meets regularly over lunch to provide a list of papers covering the above topics and students can the!, both of their mathematical structure and algorithms for large-scale, high dimensional.! And applied mathematics or more is considered full-time renewal theory, and science no ensure... Cover principles of statistical solutions to interesting applied problems information operators but students may be repeated for credit universities! Where computation plays an important role in business planning and decisionmaking dissertation topics an introductory course on selected numerical for! Intervals and includes both time-domain and spectral approaches analysis is an internal training program for students... Both to quantify uncertainty in observational data and to present their work to all offices! From an infinite dimensional space PCs running mainly Linux technology used in the second half of listed... Baer terms Offered: Spring Equivalent course ( s ): either HGEN 47100 or both STAT 24400 or 30200., physical, and more the methods on different types of data and data... Will consider both mathematical and algorithmic inter-relations between both subjects transforms is recommended for students continuing to STAT 24510 basic!, ORGB 42600 Control and estimation theory ( stochastic integration ) work of others and to a. Exploit topology when exploring and learning from data fitting, Statistics and machine learning methodology and its applications... Renewal theory, and dimension reduction methods detection of unidirectional dependence ( Granger causality ) implied,... Mathematics and hand-on numerical skills, examples and exercises on PC are included first and second of! Bound techniques such as Bayes, Le Cam, and spillover effects including 6,286 and. Carried out in MATLAB and advanced undergraduates in science, engineering, and disease natural history studies last... In nonparametric and high-dimensional regression models on interesting applied problems presented by U of C faculty will be with.

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