Statistics

2026-2027

95 courses

STATS 100Mathematics of Sports
STATS 110Introduction to Statistics for Engineering and the Sciences
STATS 116XTheory of Probability (accelerated)
STATS 117Introduction to Probability Theory
STATS 118Probability Theory for Statistical Inference
STATS 141Introduction to Statistics for Biology (BIO 141)
STATS 191Introduction to Applied Statistics
STATS 195Introduction to R
STATS 199Independent Study
STATS 200Introduction to Theoretical Statistics
STATS 200QPhilosophical Foundations of Statistics (DATASCI 200Q)
STATS 202Statistical Learning and Data Science
STATS 202FStatistical Learning and Data Science [Flipped]
STATS 202VStatistical Learning and Data Science [Virtual]
STATS 203Regression Models and Analysis of Variance
STATS 204Sampling
STATS 205Introduction to Nonparametric Statistics
STATS 206Applied Multivariate Analysis (BMDS 240)
STATS 207Time Series Analysis (STATS 307)
STATS 208Resampling Methods: Bootstrap, Cross Validation and Beyond
STATS 209Introduction to Causal Inference
STATS 211Meta-research: Appraising Research Findings, Bias, and Meta-analysis (BMDS 246, CHPR 206, EPI 206, MED 206)
STATS 214Machine Learning Theory (CS 229M)
STATS 215Statistical Models in Biology
STATS 217Introduction to Stochastic Processes I
STATS 218Introduction to Stochastic Processes II
STATS 219Stochastic Processes (MATH 136)
STATS 220Machine Learning Methods for Neural Data Analysis (CS 339N, NBIO 220, STATS 320)
STATS 221Random Processes on Graphs and Lattices
STATS 223Sequential Analysis (STATS 323)
STATS 229Machine Learning (CS 229)
STATS 232Machine Learning for Sequence Modeling (CS 229B)
STATS 250Mathematical Finance (MATH 238)
STATS 251Causal Inference in Clinical Trials and Observational Studies (BMDS 251)
STATS 260AWorkshop in Biomedical Data Science (BMDS 280A)
STATS 260BWorkshop in Biomedical Data Science (BMDS 280B)
STATS 260CWorkshop in Biomedical Data Science (BMDS 280C)
STATS 261Intermediate Biostatistics: Analysis of Discrete Data (BMDS 241, EPI 261)
STATS 262Intermediate Biostatistics: Regression, Prediction, Survival Analysis (EPI 262)
STATS 263Design of Experiments (STATS 363)
STATS 264Foundations of Statistical and Scientific Inference (BMDS 243, EPI 264)
STATS 270Bayesian Statistics (STATS 370)
STATS 271Applied Bayesian Statistics (STATS 371)
STATS 282AI and Data for Science (CS 292, EE 292R, PSYCH 292R)
STATS 285Massive Computational Experiments, Painlessly
STATS 290Computing for Data Science
STATS 292Statistical Models of Text and Language
STATS 298Industrial Research for Statisticians
STATS 299Independent Study
STATS 300ATheory of Statistics I
STATS 300BTheory of Statistics II
STATS 300CTheory of Statistics III
STATS 301Statistics Teaching Practicum
STATS 302Qualifying Exams Workshop
STATS 303Statistics Faculty Research Presentations
STATS 305AApplied Statistics I
STATS 305BApplied Statistics II
STATS 305CApplied Statistics III
STATS 307Time Series Analysis (STATS 207)
STATS 310ATheory of Probability I (MATH 230A)
STATS 310BTheory of Probability II (MATH 230B)
STATS 310CTheory of Probability III (MATH 230C)
STATS 311Information Theory and Statistics (EE 377)
STATS 314AAdvanced Statistical Theory
STATS 315AModern Applied Statistics: Learning
STATS 315BModern Applied Statistics: Learning II
STATS 317Stochastic Processes
STATS 318Modern Markov Chains (MATH 235)
STATS 319Literature of Statistics
STATS 32Introduction to R for Undergraduates
STATS 320Machine Learning Methods for Neural Data Analysis (CS 339N, NBIO 220, STATS 220)
STATS 322Function Estimation in White Noise
STATS 323Sequential Analysis (STATS 223)
STATS 324Stein's Method
STATS 325Multivariate Analysis and Random Matrices in Statistics
STATS 326Topics in Generative Modeling Methods in Protein Modeling and Design
STATS 331Survival Analysis (BMDS 252)
STATS 335The Challenge Problems Paradigm in Empirical Machine Learning and Beyond
STATS 352Topics in Computing for Data Science (BMDS 254)
STATS 354Generalization and Causality in Biohealth (CS 273D)