Course | Number | Instructor | Time | Room |
Introduction to Statistics |
S&DS 101a-109a/501a-509a |
Jonathan Reuning-Scherer and Staff |
Tues, Thurs 1:00-2:15 |
OML 202 |
Data Exploration and Analysis |
S&DS 230a/530a PLSC 530a |
Ethan Meyers |
Tues, Thurs 9:00-10:15 |
DL 220 |
(Bayesian) Probability and Statistics |
S&DS 238a/538a |
Joe Chang |
Tues, Thurs 1:00-2:15 |
ML 211 |
Probability Theory with Applications |
S&DS 241a/541a MATH 241a |
Winston Lin |
Mon, Wed 9:00-10:15 |
SSS 114 |
Linear Models |
S&DS 312a/612a |
David Brinda |
Mon, Wed 11:35-12:50 |
WLH 116 |
Measuring Impact and Opinion Change |
S&DS 315a/PLSC 340a |
Josh Kalla |
Tues, Thurs 2:30-3:45 |
TBD |
Introduction to Data Mining and Machine Learning |
S&DS 355a/555a |
John Lafferty |
Tues, Thurs 9:00-10:15 |
OML 202 |
Applied Data Mining and Machine Learning |
S&DS 365a/565a |
Derek Feng |
Tues, Thurs 9:00-10:15 |
LC 101 |
Statistical Inference |
S&DS 410a/610a |
Zhou Fan |
Tues, Thurs 11:35-12:50 |
WTS B52 |
Optimization Techniques |
S&DS 430a/630a ENAS 530a EENG 437a ECON 413a |
Sekhar Tatikonda |
Tues, Thurs 1:00-2:15 |
WTS A51 |
Senior Project |
S&DS 491a |
Sekhar Tatikonda |
- |
- |
Time Series with R/Python |
S&DS 583 |
Dhafer Malouche |
Mon, Wed 2:30-3:45 |
24 Hillhouse |
Selected Topics in Statistical Decision Theory |
S&DS 411a/611a |
Harrison Zhou |
Wed 9:00 - 11:15 |
24 Hillhouse |
Statistical Case Studies |
S&DS 625a |
Jay Emerson |
Mon, Wed 1:00-2:15 |
WTS A74 |
Equity in AI Systems |
S&DS 650a |
Elisa Celis |
Tues 1:30-3:20 |
24 Hillhouse |
Computational Mathematics for Data Science |
S&DS 663a |
Roy Lederman |
Mon, Wed 11:35-12:50 |
24 Hillhouse |
Indep Study |
S&DS 480ab |
Staff |
- |
- |
Practical Work |
S&DS 626ab |
DGS |
- |
- |
Statistical Consulting |
S&DS 627a/628b |
Jay Emerson |
Fri 2:30-4:30 |
24 Hillhouse |
Independent Study or Topics Course |
S&DS 690ab |
DGS |
- |
- |
Research Seminar in Probability |
S&DS 699ab |
Sekhar Tatikonda and David Pollard |
Fri 11:00-1:00 |
24 Hillhouse |
Departmental Seminar |
S&DS 700ab |
- |
Mon 4:00-5:30 |
24 Hillhouse |
Introductory Statistics |
S&DS 100b/500b |
Ethan Meyers |
Tues, Thurs 9:00-10:15 |
TBD |
YaleData |
S&DS 123b |
Jessi Cisewski |
Mon, Wed, Fri 10:30-11:20 |
Luce 101 |
Foreign Assistance to Sub-Saharan Africa: Archival Data Analysis |
S&DS 138b/AFST 378/EVST 378/AFST 570 |
Russell Barbour |
Tues, Thurs 2:30-3:45 |
WTS A74 |
YData: Text Data Science: An Introduction |
S&DS 171b/571b |
Derek Feng |
Thurs 9:25-11:15 |
LC 208 |
YData: Data Science for Political Campaigns |
S&DS 172b/572b PLSC347b/524b |
Joshua Kalla |
Thurs 9:25-11:15 |
LC 104 |
YData: Analysis of Baseball Data |
S&DS 173b/573b |
Ethan Meyers |
Wed 1:30-3:20 |
TBD |
Intensive Introductory Statistics and Data Science |
S&DS 220b/520b |
Joe Chang |
Tues, Thurs 9:00-10:15 |
WLH 119 |
Data Exploration and Analysis |
S&DS 230b/530b PLSC 530b |
Jonathan Reuning-Scherer |
Tues, Thurs 9:00-10:15 |
Davies Aud. |
Probability for Data Science |
S&DS 240b/540b |
Harrison Zhou |
Mon, Wed 1:00-2:15 |
TBD |
Theory of Statistics |
S&DS 242b/542b |
Zhou Fan |
Mon, Wed 9:00-10:15 |
Davies |
Computational Tools for Data Science |
S&DS 262b/562b |
Roy Lederman |
Mon, Wed 11:35-12:50 |
TBD |
Introduction to Causal Inference |
S&DS 314b |
Winston Lin |
Tues, Thurs 4:00-5:15 |
TBD |
Stochastic Processes |
S&DS 351b/551b |
Amin Karbasi |
Mon, Wed 1:00-2:15 |
WLH 119 |
Data Analysis |
S&DS 361b/661b |
Joe Chang |
Mon, Wed 2:30-3:45 |
ML 211 |
Multivariate Statistics for Social Sciences |
S&DS 363b/563b |
Jonathan Reuning-Scherer |
Tues, Thurs 1:00-2:15 |
KRN 301 |
Information Theory |
S&DS 364b/664b |
Andrew Barron |
Tues, Thurs 11:35-12:50 |
24 Hillhouse |
Applied Data Mining and Machine Learning |
S&DS 365b/665b |
Derek Feng |
Mon, Wed 11:35-12:50 |
LC 101 |
Advanced Probability |
S&DS 400b/600b MATH 330b |
Sekhar Tatikonda |
Tues, Thurs 2:30-3:45 |
ML 211 |
Senior Capstone: Statistical Case Studies |
S&DS 425b |
Jay Emerson |
Mon, Wed 2:30-3:45 |
17 Hillhouse Room 101 (TEAL) |
Senior Seminar and Project |
S&DS 490b |
TBD or not offered |
TBD |
24 Hillhouse Room 107 |
Topics in Deep Learning: Methods and Biomedical Applications |
S&DS 567 CB&B 567 |
Martin Renqiang and Mark Gerstein |
Mon 9:00-11:15 |
TBD |
Computation and Optimization |
S&DS 631 |
Dan Spielman |
Tues, Thurs 1:00-2:15 |
TBD |
Theory of Deep Learning |
S&DS 670a |
Andrew Barron |
Mon, Wed 9:00-10:15 |
24 Hillhouse |
Applied Spatial Statistics |
S&DS 674b/F&ES 781b |
Tim Gregoire |
Tues, Thurs 10:30-11:50 |
KRN G01 |
An Introduction to R for Statistical Computing and Data Science (1/2 credit) |
S&DS 150/510a |
not taught this year |
Statistics and Data Science Computing Laboratory (1/2 credit) |
S&DS 110b/510b |
not taught this year |
Data Science Ethics |
S&DS 150b |
not taught this year |
YData: ExoStatistics: Exploring Extrasolar Planets with Data
Science |
S&DS 170b570b |
not taught this year |
Theory of Probability and Statistics |
S&DS 239a/539a |
not taught this year |
Design and Analysis of Algorithms |
CPSC 365b |
not taught this year |
Senior Seminar and Project |
S&DS 490a |
not taught this year |
Senior Project |
S&DS 492b |
not taught this year |
Research Design and Causal Inference |
PLSC 508b |
not taught this year |
Applied Linear Models |
S&DS 531a |
not taught this year |
Intensive Algorithms |
S&DS 566 |
not taught this year |
Introduction to Random Matrix Theory and Applications |
S&DS 615b |
not taught this year |
Statistical Computing |
S&DS 662b |
not taught this year |
Spectral Graph Theory |
CPSC 662a |
not taught this year |
Probabilistic Networks, Algorithms, and Applications |
S&DS 667a |
not taught this year |
Nonparametric Estimation and Machine Learning |
S&DS 468b |
not taught this year |
Statistical Learning Theory |
S&DS 669b |
not taught this year |
Topics on Random Graphs |
MATH 670 |
not taught this year |
Information Theory Tools in Probability and Statistics |
S&DS 672a |
not taught this year |
Signal Processing for Data Science |
S&DS 676b |
not taught this year |
High-Dimensional Statistical Estimation |
S&DS 679a |
not taught this year |
Statistical Methods in Neuroimaging |
S&DS 683a |
not taught this year |
Statistical Inference on Graphs |
S&DS 684a |
not taught this year |
Placeholder -- Monograph |
706 |
not taught this year |