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
Meghan Hutch
Sec 1: MWF 9:30 AM–10:20 AM
Harper Memorial 140
Introduction to Data Science I
STAT 11800=DATA 11800
Kelly Smalenberger
Sec 2: MWF 10:30 AM–11:20 AM
Ryerson 251
Introduction to Data Science I
STAT 11800=DATA 11800
William Trimble
Sec 3: TR 9:30 AM–10:50 AM
Hinds 101
Introduction to Data Science II
STAT 11900=DATA 11900
Amy Nussbaum
Sec 1: TR 9:30 AM–10:50 AM
Crerar 011
Elementary Statistics
STAT 20000
Yibi Huang
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
Rosenwald 015
Statistical Methods and Applications
STAT 22000
Fei Liu
Sec 2: MWF 9:30 AM–10:20 AM
Ryerson 277
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
Daniel Xiang
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: MW 3:00 PM–4:20 PM
BSLC 109
Statistical Models and Methods I
STAT 23400
TBA
Sec 1: Cancelled
TBA
Statistical Models and Methods I
STAT 23400
Yibi Huang
Sec 2: MWF 10:30 AM–11:20 AM
Eckhart 133
Numerical Linear Algebra
STAT 24300
Yuxin Zhou
Sec 1: MWF 11:30 AM–12:20 PM
Rosenwald 015
Statistical Theory and Methods I
STAT 24400
Jiaqi Li
Sec 1: TR 2:00 PM–3:20 PM
Kent 120
Statistical Theory and Methods Ia
STAT 24410=STAT 30030
Dan Nicolae
Sec 1: TR 2:00 PM–3:20 PM
Eckhart 133
Causal Inference Methods And Case Studies
STAT 24630
Jingshu Wang
Sec 1: TR 12:30 PM–1:50 PM
Eckhart 133
Introduction to Mathematical Probability
STAT 25100
Yuxin Zhou
Sec 1: MWF 9:30 AM–10:20 AM
Eckhart 133
Introduction to Mathematical Probability
STAT 25100
Siyao Yang
Sec 2: TR 11:00 AM–12:20 PM
Rosenwald 015
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Rebecca Willett
Sec 1: TR 9:30 AM–10:50 PM
Ryerson 251
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Tian Li
Sec 2: MW 1:30 PM–2:50 PM
Eckhart 202
Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Tian Li
Sec 3: MW 3:00 PM–4:20 PM
Eckhart 202
Machine Learning
STAT 27725=CMSC 25400
Risi Kondor
Sec 1: TR 9:30 AM–10:50 AM
Stuart 105
Practical R Programming
STAT 27815
Ryan McShane
Sec 1: MW 1:30 PM–2:50 PM
Jones 303
Hypothesis Testing with Empirical Bayes Methodology
STAT 27855
Daniel Xiang
Sec 1: TR 11:00 AM–12:20 PM
Jones 226
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
Eckhart 133
Distribution Theory
STAT 30400
Rina Barber
Sec 1: MW 9:00 AM-10:20 AM
Jones 303
Asymptotic Theory for Time Series Analysis and Stochastic Approximation Algorithms
STAT 30815
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
Eckhart 133
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
Eckhart 133
Introduction to Stochastic Processes I
STAT 31200
Wei Biao Wu
Sec 1: TR 9:30 AM–10:50 AM
Jones 303
Applied Dynamical Systems
STAT 31410=CAAM 31410
Nisha Chandramoorthy and Mary Silber
Sec 1: TR 11:00 AM-12:20 PM
Kersten 101
Applied Linear Algebra
STAT 31430=CAAM 31430
Eric Baer
Sec 1: MW 1:30 PM–2:50 PM
Ryerson 177
Applied Analysis
STAT 31440=CAAM 31440
Eric Baer
Sec 1: MW 10:30 AM–11:50 AM
Jones 226
Applied Complex Analysis
STAT 31470=CAAM 21470, CAAM 31470
Timonthy Roberts
Sec 1: MWF 12:30 PM–1:20 PM
Ryerson 255
Asymptotic Analysis
STAT 31531=CAAM 31531
Jeremy Hoskins
Sec 1: TR 2:00 PM–3:20 PM
Ryerson 176
Probability and Statistics
STAT 32400=BUSN 41901
Tetsuya Kaji
Sec 50: F 1:30 PM–4:20 PM
Charles M. Harper Center C01
Randomness and High-Dimensional Optimization
STAT 33612
Frederic Koehler
Sec 1: TR 12:30 PM–1:50 PM
Jones 303
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 3:30 PM–4:50 PM
Cobb 409
Genomic Evolution I
STAT 35410=ECEV 35901, EVOL 35901
Manyuan Long
Sec 1: W 3:30 PM–5:20 PM
Zoology 302
Statistical Applications
STAT 35800=PBHS 33500, CHDV 32702
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 11:00 AM-12:20 PM
Ryerson 276
Topics in Deep Learning: Generative Models
STAT 37792
Yali Amit
Sec 1: MW 1:30 PM-2:50 PM
Pick 022
Practical R Programming with Extensions
STAT 37815
Ryan McShane
Sec 1: MW 3:00 PM-4:20 PM
Jones 303
Scientific Computing with Python
STAT 37830=CAAM 37830
Tristan Goodwill
Sec 1: TR 11:00 AM-12:20 PM
Jones 303
Master's Seminar
STAT 39900
Mei Wang
Sec 1
Reading and Research: Statistics
STAT 40100
Topics in Distribution-Free Inference
STAT 41521
Rina Barber
Sec 1: MW 1:30 PM–2:50 PM
Jones 226
Consulting in Statistics
STAT 44100
Claire Donnat and Mei Wang
Sec 1: W 12:00 PM-1:00 PM
Searle 236