Spring 2022 Course Offerings

Please note that these course listings are subject to change.

Introduction to Data Science II 
STAT 11900=DATA 11900, CMSC 11900
William Trimble
Sec 1: TR 9:30 AM–10:50 AM
Hinds 101

Elementary Statistics
STAT 20000
Kendra Burbank
Sec 1: MWF 10:30 AM–11:20 AM
Rosenwald 011

Statistical Methods and Applications
STAT 22000
Fei Liu
Sec 1: MWF 9:30 AM–10:20 AM
Eckhart 133

Statistical Methods and Applications
STAT 22000
Mary Silber
Sec 2: MWF 10:30 AM–11:20 AM
Eckhart 133

Linear Models and Experimental Design
STAT 22200
Yibi Huang
Sec 1: MWF 10:30 AM-11:20 AM
Kent 120

Applied Regression Analysis
STAT 22400=PBHS 32400
Kendra Burbank
Sec 1: MW 1:30 PM-2:50 PM
Eckhart 133

Biostatistical Methods
STAT 22700
Lin Chen
Sec 1: TR 12:30 PM-1:50 PM
BSLC 324

Statistical Models and Method 1
STAT 23400
Yier Lin
Sec 1: TR 11:00 AM-12:20 PM
Eckhart 133

Statistical Models and Method 1
STAT 23400
Daniel Zhang
Sec 2: TR 12:30 PM-1:50 PM
Eckhart 133

Statistical Models and Method 1
STAT 23400
Chih-Hsuan Wu
Sec 3: TR 2:00 PM-3:20 PM
Eckhart 133

Statistical Theory and Method 2
STAT 24500
Mihai Anitescu
Sec 1: MW 1:30 PM–2:50 PM
CLSC 101

Multivariate Statistical Analysis: Applications and Techniques
STAT 24620=STAT 32950
Mei Wang
Sec 1: TR 9:30 AM–10:50 AM
Kent 107

Causal Inference Methods and Case Studies
STAT 24630
Jingshu Wang
Sec 1: TR 3:30 PM–4:50 PM
Eckhart 308

Introduction to Mathematical Probability 
STAT 25100
Yi Sun
Sec 1: MW 1:30 PM–2:50 PM
Hinds 101

Introduction to Mathematical Probability 
STAT 25100
Zhongjian Wang
Sec 2: MW 3:00 PM–4:20 PM
Hinds 101

Introduction to Mathematical Probability-A
STAT 25150
Robert Fefferman
Sec 1: TR 9:30 AM–10:50 AM
Eckhart 133

Introduction to Bayesian Data Analysis
STAT 27410
Fei Liu
Sec 1: MWF 11:30 AM-12:20 PM
Stuart 104

Mathematical Foundations of Machine Learning
STAT 27700=CMSC 25300, CMSC 35300
Eric Jonas
Sec 1: MW 3:00 PM-4:20 PM 
Ryerson 178

Further Topics in Machine Learning
STAT 27750
Victor Veitch
Sec 1: TR 11:00 AM-12:20 PM 
Ryerson 255

Optimization
STAT 28000=CAAM 28000
Lek-Heng Lim
Sec 1: MW 3:00 PM-4:20 PM 
Eckhart 133

Undergrad Research: Statistics
STAT 29700
Mary Sara McPeek

Bachelor's Paper: Statistics
STAT 29900
Mary Sara McPeek

Mathematical Statistics II
STAT 30200
Claire Donnat
Sec 1: TR 2:00 PM-3:20 PM
Eckhart 117

High Dimensional Time Series Analysis
STAT 30810
Wei Biao Wu
Sec 1: MWF 9:30 AM-10:20 AM
Cobb 119

Partial Differential Equations
STAT 31220=CAAM 31220
Guillaume Bal
Sec 1: TR 2:00 PM-3:20 PM
Jones 226

Variational Methods in Image Processing
STAT 31240=CAAM 31240
Eric Baer
Sec 1: MW 9:00 AM-10:20 AM
Jones 226

Applied Partial Differential Equations
STAT 31450=CAAM 31450
Jeremy Hoskins
Sec 1: MW 10:30 AM-11:50 AM
Jones 226

Monte Carlo Simulation
STAT 31511=CAAM 31511
Daniel Sanz-Alonso
Sec 1: TR 11:00 AM-12:20 PM
Harper 130

Multivariate Statistical Analysis: Applications and Techniques
STAT 32950=STAT 24620
Mei Wang
Sec 1: TR 9:30 AM–10:50 AM
Kent 107

Bayesian Statistical Inference and Machine Learning
STAT 33400=FINM 33200
Staff
Sec 1: F 1:30 PM–4:20 PM
Kent 107
 
Modern Methods in Applied Statistics
STAT 34800
Matthew Stephens
Sec 1: TR 3:30 PM–4:50 PM
Eckhart 133
 
Fundamentals of Computational Biology: Algorithms and Applications
STAT 35460
Mengjie Chen and Xin He
Sec 1: MW 1:30 PM–2:50 PM 
BSLC 305

Statistical Genetics
STAT 35500
Mary Sara McPeek
Sec 1: W 1:30 PM-4:20 PM
Jones 303

Applied Bayesian Modeling and Inference
STAT 35920=PBHS 43010
Yuan Ji
Sec 1: TR 12:30 PM–1:50 PM 
BSLC 313

Machine Learning and Large-Scale Data Analysis
STAT 37601=CMSC 25025
Yali Amit
Sec 1: TR 2:00 PM-3:20 PM
Ryerson 251

Machine Learning
STAT 37710=CAAM 37710, CMSC 35400
Yuxin Chen
Sec 1: TR 9:30 AM-10:50 PM
Stuart 102

Machine Learning on Graphs, Groups, and Manifolds
STAT 37788
Risi Kondor
Sec 1: MW 1:30 PM-2:50 PM
Ryerson 176

Topics in Machine Learning: Learning in Games
STAT 37789
Alexander Strang
Sec 1: TR 9:30 AM-10:50 AM
Jones 226

Topics in Deep Learning: Discriminative Models
STAT 37793
Yi Sun
Sec 1: MW 3:00 PM-4:20 PM
Jones 226

Causal Inference with Machine Learning
STAT 37795
Victor Veitch
Sec 1: TR 3:30 PM-4:50 PM
Jones 226

Measure-Theoretic Probability III
STAT 38300
Per Mykland
Sec 1: TR 11:00 AM-12:20 PM
Jones 226
 
Stochastic Calculus
STAT 39000=FINM 34500
Greg Lawler
Sec 1: MW 3:00 PM-4:20 PM
Kent 107

Stochastic Calculus I
STAT 39010=FINM 34510
Greg Lawler
Sec 1: MW 3:00 PM-4:20 PM
Kent 107

Stochastic Calculus II
STAT 39020=FINM 34520
Greg Lawler
Sec 1: MW 3:00 PM-4:20 PM
Kent 107

Master's Seminar: Statistics
STAT 39900
Mei Wang

Reading and Research: Statistics
STAT 40100
 
Theoretical Neuroscience: Statistics and Information Theory
STAT 42600=CPNS 35600, ORGB 42600
Stephanie Palmer
Sec 1: TR 9:30 AM-10:50 AM
Kent 103

Consulting in Statistics
STAT 44100
Mei Wang and Claire Donnat
Sec 1: W 12:00 PM-1:00 PM
Jones 303