Course  Number   Instructor  Time  Room 
Introduction to Statistics 
101a106a/501a506a 

Jonathan ReuningScherer and Staff 
Tues, Thurs 1:002:15 
OML 202 
Data Exploration and Analysis 
230a/530a/PLSC 530a 

Susan Wang 
Tues, Thurs 9:0010:15 
DL 220 
(Bayesian) Probability and Statistics 
238a/538a 

Joe Chang 
Tues, Thurs 1:002:15 
ML 211 
Probability Theory with Applications 
241a/541a/MATH 241a 

Yihong Wu 
Mon, Wed 9:0010:15 
Davies Aud 
Linear Models 
312a/612a 

David Brinda 
Mon, Wed 11:3512:50 
WTS A60 
Introduction to Causal Inference 
314a 

Winston Lin 
Tues, Thurs 4:005:15 
24 Hillhouse Rm 107 
Applied Data Mining and Machine Learning 
365a/565a 

John Lafferty and Derek Feng 
Tues, Thurs 9:0010:15 
WLH 201 
Statistical Inference 
410a/610a 

Zhou Fan 
Tues, Thurs 11:3512:50 
24 Hillhouse Rm 107 
Optimization Techniques 
430a/630a/ENAS 530a/EENG 437a/ECON 413a 

Sekhar Tatikonda 
Tues, Thurs 1:002:15 
WLH 117 
Statistical Case Studies 
625a 

Susan Wang 
Mon, Wed 1:002:15 
WTS A74 
Computational Mathematics for Data Science 
663a 

Roy Lederman 
TBD 
TBD 
Information Theory Tools in Probability and Statistics 
672a 

Andrew Barron 
TBD 
24 Hillhouse Rm 107 
HighDimensional Statistical Estimation 
679a 

Sahand 
Tues 2:305:00 pm 
24 Hillhouse Rm 107 
Statistical Methods in Neuroimaging 
683a 

Dustin Scheinost and Joe Chang 
TBD 
24 Hillhouse Room 107 
Statistical Inference on Graphs 
684a 

Yihong Wu 
Wed 2:305:00 pm 
24 Hillhouse Rm 107 
Spectral Graph Theory 
CPSC 662a 

Dan Spielman 
Mon, Wed 2:303:45 
TBD 
Individual Studies 
480ab 

Staff 
 
 
Practical Work 
626b 

DGS 
 
 
Statistical Consulting 
627a/628b 

Derek Feng 
Fri 2:304:30 
24 Hillhouse Rm 107 
Independent Study or Topics Course 
690ab 

DGS 
 
 
Research Seminar in Probability 
699ab 

Sekhar Tatikonda and David Pollard 
Fri 11:001:00 
24 Hillhouse Rm 107 
Departmental Seminar 
700ab 

 
Mon 4:155:30 
24 Hillhouse Rm 107 
Introductory Statistics 
100b/500b 

David Brinda 
Mon, Wed, Fri 10:3011:20 
TBA 
YaleData 
123b 

Jessi Cisewski 
TBD 
TBD 
YData: Lab Course 
124b 

Jessi Cisewski 
TBD 
TBD 
Intensive Introductory Statistics and Data Science 
220b/520b 

Susan Wang 
Tues, Thurs 9:0010:15 
TBA 
Data Exploration and Analysis 
230b/530b/PLSC 530b 

Jonathan ReuningScherer 
Tues, Thurs 9:0010:15 
TBA 
Theory of Statistics 
242b/542b 

Andrew Barron 
Mon, Wed, Fri 9:2510:15 
TBA 
Computational Tools for Data Science 
262b/562b 

Sahand? Bracketed? 
TBD 
TBD 
Stochastic Processes 
351b/551b 

Yihong Wu and Sahand 
Mon, Wed 1:002:15 
TBA 
Data Analysis 
361b/661b 

David Brinda 
Mon, Wed 2:303:45 
TBA 
Multivariate Statistics for Social Sciences 
363b/563b 

Jonathan ReuningScherer 
Tues, Thurs 1:002:15 
KRN 301 
Information Theory 
364b/664b 

Andrew Barron 
Tues, Thurs 11:3512:50 
24 Hillhouse Rm 107 
Applied Data Mining and Machine Learning 
365b/665b 

Derek Feng 
Mon, Wed 11:3512:50 
SCL 160 
Advanced Probability 
400b/600b/MATH 330b 

Sekhar Tatikonda 
Tues, Thurs 2:303:45 
24 Hillhouse Rm 107 
Senior Capstone: Statistical Case Studies 
425b 

Susan Wang 
Tues, Thurs 11:3512:50 
TBA 
Introduction (?) to Random Matrix Theory and Applications 
615b 

Zhou Fan 
Tues Thur 1:002:15 pm 
24 Hillhouse Rm 107 
Statistical Methods in Computational Biology 
645b 

Hongyu Zhao 
Thur 1:002:50 pm 
TBD 
Statistical Learning Theory 
669b 

Sahand Negahban 
Mon, Wed, 2:303:45 
24 HH Room 107 
Selected Topics in Neural Nets 
671b 

Harrison Zhou 
Wed 9:0011:30 (tentative) 
24 Hillhouse Rm 107 
Applied Spatial Statistics 
674b/F&ES 781b 

Tim Gregoire 
Tues, Thurs 10:3011:50 
TBD 
Design and Analysis of Algorithms 
CPSC 365b 

Daniel Spielman 
Tues, Thurs 2:303:45 
DL 220 
Research Design and Causal Inference 
PLSC 508b 

Winston Lin 
TBD 
TBD 
An Introduction to R for Statistical Computing and Data Science (1/2 credit) 
110a/510a 
 
not taught this year   
Applied Linear Models 
531a 
 
not taught this year   
Probabilistic Networks, Algorithms, and Applications 
667a 
 
not taught this year   
Statistics and Data Science Computing Laboratory (1/2 credit) 
110b/510b 
 
not taught this year   
Nonparametric Estimation and Machine Learning 
468b 
 
not taught this year   
Senior Seminar and Project 
490b 
 
not taught this year   
Statistical Computing 
662b 
 
not taught this year   