Undergraduate Statistics Course List Graduate Statistics Course List Course Search
Please note that these course listings are subject to change.
Introduction to Data Science I
STAT 11800=DATA 11800
Susanna Lange
Sec 1: TR 9:30 AM–10:50 AM
Ryerson 251
Introduction to Data Science I
STAT 11800=DATA 11800
Staff
Sec 2: Cancelled
TBA
Introduction to Data Science I
STAT 11800=DATA 11800
Staff
Sec 3: Cancelled
TBA
Introduction to Data Science I
STAT 11800=DATA 11800
Mario Banuelos
Sec 4: MWF 9:30 AM–10:20 AM
Stuart 102
Introduction to Data Science II
STAT 11900=DATA 11900
David Biron
Sec 1: TR 9:30 AM–10:50 AM
Ryerson 277
Elementary Statistics
STAT 20000
Claire Tseng
Sec 1: MWF 12:30 PM–1:20 PM
Eckhart 133
Statistical Methods and Applications
STAT 22000
Kendra Burbank
Sec 1: MWF 9:30 AM–10:20 AM
Eckhart 133
Statistical Methods and Applications
STAT 22000
Fei Liu
Sec 2: MWF 9:30 AM–10:20 PM
Stuart 105
Statistical Methods and Applications
STAT 22000
Kendra Burbank
Sec 3: MWF 11:30 AM–12:20 PM
Eckhart 133
Statistical Methods and Applications
STAT 22000
Fei Liu
Sec 4: MWF 11:30 AM–12:20 PM
Stuart 105
Applied Regression Analysis
STAT 22400=PBHS 32400
Yibi Huang
Sec 1: MWF 1:30 PM–2:20 PM
Eckhart 133
Epidemiology and Population Health
STAT 22810=ENST 27400, HLTH 20910, PBHS 30910, PPHA 36410
Diane Lauderdale
Sec 1: TR 3:30 PM–4:50 PM
BSLC 109
Statistical Models and Methods I
STAT 23400
Daniel Xiang
Sec 1: MWF 9:30 AM–10:20 AM
Rosenwald 011
Statistical Models and Methods I
STAT 23400
Daniel Xiang
Sec 2: MWF 10:30 AM–11:20 AM
Rosenwald 011
Numerical Linear Algebra
STAT 24300
Anjali Nair
Sec 1: TR 12:30 PM–1:50 PM
Pick 016
Statistical Theory and Methods I
STAT 24400
Mei Wang
Sec 1: TR 2:00 PM–3:20 PM
Eckhart 133
Statistical Theory and Methods Ia
STAT 24410=STAT 30030
Dan Nicolae
Sec 1: TR 2:00 PM–3:20 PM
Hinds 101
Causal Inference Methods And Case Studies
STAT 24630
Jingshu Wang
Sec 1: TR 12:30 PM–1:50 PM
Jones 226
Introduction to Mathematical Probability
STAT 25100
Thuyen Dang
Sec 1: TR 11:00 AM–12:20 PM
MS 112 (5727 S. University Ave)
Introduction to Mathematical Probability
STAT 25100
Siyao Yang
Sec 2: TR 12:30 PM–1:50 PM
Eckhart 133
Time Dependent Data
STAT 26100=STAT 33600
Wei Biao Wu
Sec 1: TR 9:30 AM–10:50 AM
Eckhart 133
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Bo Li
Sec 1: MW 1:30 PM–2:50 PM
Hinds 101
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Michael Maire
Sec 2: MW 3:00 PM–4:20 PM
Eckhart 133
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Michael Maire
Sec 3: MW 4:30 PM–5:50 PM
Eckhart 133
Practical R Programming
STAT 27815
Ryan McShane
Sec 1: MW 1:30 PM–2:50 PM
Jones 303
Undergraduate Research
STAT 29700
Yibi Huang
Sec 1
Bachelor's Paper
STAT 29900
Yibi Huang
Sec 1
Statistical Theory and Methods Ia
STAT 30030=STAT 24410
Dan Nicolae
Sec 1: TR 2:00 PM–3:20 PM
Hinds 101
Distribution Theory
STAT 30400
Wei Biao Wu
Sec 1: MW 9:00 AM-10:20 AM
Jones 226
Mathematical Computation I: Matrix Computation Course
STAT 30900=CAAM 30900, CMSC 37810
Lek-Heng Lim
Sec 1: MW 3:00 PM–4:20 PM
Stuart 101
Modern Applied Optimization
STAT 31001=FINM 34800, CAAM 31001
Lek-Heng Lim
Sec 1: T 12:30 PM-3:20 PM
MS 112 (5727 S. University Ave)
Inverse Problems and Data Assimilation: A Machine Learning Approach
STAT 31151=CAAM 31151
Daniel Sanz-Alonso
Sec 1: TR 9:30 AM–10:50 AM
Harper Memorial 130
Fast Algorithms
STAT 31190=CAAM 31190
Jeremy Hoskins
Sec 1: TR 2:00 PM–3:20 PM
Jones 226
Foundations Of Computational Dynamics
STAT 31310=CAAM 31310
Nisha Chandramoorthy
Sec 1: MW 1:30 PM–2:50 PM
Ryerson 255
Applied Dynamical Systems
STAT 31410=CAAM 31410
Mary Silber
Sec 1: TR 11:00 AM-12:20 PM
Jones 226
Applied Linear Algebra
STAT 31430=CAAM 31430
Eric Baer
Sec 1: MW 3:00 PM–4:20 PM
Ryerson 177
Applied Analysis
STAT 31440=CAAM 31440
Eric Baer
Sec 1: MWF 10:30 AM–11:20 AM
Eckhart 133
Probability and Statistics
STAT 32400=BUSN 41901
Tetsuya Kaji
Sec 50: F 1:30 PM–4:20 PM
Charles M. Harper Center C04
Sample Surveys
STAT 33100
Kirk Wolter
Sec 1: MW 10:30 AM-11:50 AM
Jones 226
Time Dependent Data
STAT 33600=STAT 26100
Wei Biao Wu
Sec 1: TR 9:30 AM–10:50 AM
Eckhart 133
Applied Linear Statistical Methods
STAT 34300
Nikolaos Ignatiadis
Sec 1: TR 11:00 AM–12:20 PM
Eckhart 133
Introduction to Clinical Trials
STAT 35201=PBHS 32901
Mei-Yin Chen Polley
Sec 1: TR 2:00 PM-3:20 PM
BSLC 202
Statistical Applications
STAT 35800=CHDV 32702, PBHS 33500
Robert Gibbons
Sec 1: MW 1:30 PM-2:50 PM
BSLC 240
Foundations of Machine Learning and AI - Part I
STAT 37711=CAAM 37711, DATA 37711
Victor Veitch
Sec 1: TR 3:30 PM-4:50 PM
Stuart 102
Algorithms for Massive Datasets
STAT 37782=CAAM 37782
Yuehaw Khoo
Sec 1: MW 3:00 PM–4:20 PM
Jones 226
Topics in Deep Learning: Generative Models
STAT 37792
Yali Amit
Sec 1: MW 1:30 PM-2:50 PM
Jones 226
Practical R Programming with Extensions
STAT 37815
Ryan McShane
Sec 1: MW 9:30 AM-10:50 AM
Jones 303
Scientific Computing with Python
STAT 37830=CAAM 37830
Tristan Goodwill
Sec 1: TR 3:30 PM-4:50 PM
Eckhart 133
Brownian Motion and Stochastic Calculus
STAT 38510=MATH 38511
Greg Lawler
Sec 1: MWF 9:30 AM–10:20 AM
Rosenwald 015
Topics In Random Matrix Theory
STAT 38520=CAAM 38520
Yuxin Zhou
Sec 1: TR 9:30 AM–10:50 AM
Jones 226
Master's Seminar
STAT 39900
Mei Wang
Sec 1
Reading and Research: Statistics
STAT 40100
High-Dimensional Statistics I
STAT 41500
Sagnik Nandy
Sec 1: TR 11:00 AM–12:20 PM
Jones 303
Consulting in Statistics
STAT 44100
Claire Donnat and Mei Wang
Sec 1: W 12:00 PM-1:00 PM
Jones 303