Title  Instructor(s)  Quarter  Day, Time, Location 

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 1) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 10:00am  10:50am 420040 

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 2) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 9:00am  9:50am 420040 

Mathematics in the Real World (MATH 16) STATS 90 (section 1) Introduction to noncalculus applications of mathematical ideas and principles in realworld problems. Topics include probability and counting, basic statistical concepts... 
Poulson, J.  20142015 Spring 
Monday Wednesday Friday 9:00am  9:50am 380380W 
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Bacallado, S., Mukherjee, R.  20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 10:00am  10:50am 420040 
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Bacallado, S., Mukherjee, R.  20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 10:00am  10:50am 420040 
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 2) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Bacallado, S., Mukherjee, R.  20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 9:00am  9:50am 420040 
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 2) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Bacallado, S., Mukherjee, R.  20142015 Spring 
Monday Tuesday Wednesday Thursday Friday 9:00am  9:50am 420040 
Introduction to R (CME 195) STATS 195 (section 1) This short course runs for the first four weeks of the quarter and is offered in the fall. It is recommended for students who want to use R in statistics, science, or... 
Suo, X.  20142015 Spring 
Monday Wednesday 4:30pm  5:45pm Hewlett Teaching Center 103 
Introduction to Regression Models and Analysis of Variance STATS 203 (section 1) Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable... 
Kaluwa Devage, P.  20142015 Spring 
Tuesday Thursday 10:15am  11:30am 380380F 
Introduction to Regression Models and Analysis of Variance STATS 203 (section 1) Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable... 
Kaluwa Devage, P.  20142015 Spring 
Tuesday Thursday 10:15am  11:30am 380380F 
Introduction to Time Series Analysis STATS 207 (section 1) Time series models used in economics and engineering. Trend fitting, autoregressive and moving average models and spectral analysis, Kalman filtering, and statespace... 
Donoho, D.  20142015 Spring 
Tuesday Thursday 2:15pm  3:30pm 380380F 
Introduction to the Bootstrap STATS 208 (section 1) The bootstrap is a computerbased method for assigning measures of accuracy to statistical estimates. By substituting computation in place of mathematical formulas, it... 
Donoho, D.  20142015 Spring 
Tuesday Thursday 9:00am  10:15am 5052H 
Introduction to Stochastic Processes STATS 218 (section 1) Renewal theory, Brownian motion, Gaussian processes, second order processes, martingales. 
Romano, J.  20142015 Spring 
Tuesday Thursday 9:30am  10:45am 320220 
Mathematical and Computational Finance Seminar (CME 242) STATS 239 (section 1) 
Jain, K.  20142015 Spring 
Wednesday 4:15pm  5:30pm 200303 
Workshop in Biostatistics (HRP 260C) STATS 260C (section 1) Applications of statistical techniques to current problems in medical science. To receive credit for one or two units, a student must attend every workshop. To receive two... 
Olshen, R., Sabatti, C.  20142015 Spring 
Thursday 1:15pm  3:05pm MSOBX303 
Intermediate Biostatistics: Regression, Prediction, Survival Analysis (HRP 262) STATS 262 (section 1) Methods for analyzing longitudinal data. Topics include KaplanMeier methods, Cox regression, hazard ratios, timedependent variables, longitudinal data structures,... 
Sainani, K.  20142015 Spring 
Monday 3:00pm  4:30pm Li Ka Shing Center, room 120 
Intermediate Biostatistics: Regression, Prediction, Survival Analysis (HRP 262) STATS 262 (section 2) Methods for analyzing longitudinal data. Topics include KaplanMeier methods, Cox regression, hazard ratios, timedependent variables, longitudinal data structures,... 
Sainani, K.  20142015 Spring 
Wednesday 3:15pm  4:45pm Li Ka Shing Center, room 120 
A Course in Bayesian Statistics (STATS 370) STATS 270 (section 1) Advancedlevel Bayesian statistics. Topics: Discussion of the mathematical and theoretical foundation for Bayesian inferential procedures. Examination of the construction... 
Wong, W.  20142015 Spring 
Monday Wednesday 9:30am  10:45am 200107 
Theory of Statistics STATS 300C (section 1) Decision theory formulation of statistical problems. Minimax, admissible procedures. Complete class theorems ("all" minimax or admissible procedures are "Bayes"), Bayes... 
Candes, E.  20142015 Spring 
Monday Wednesday Friday 11:00am  11:50am Sequoia Hall 200 
PhD First Year Student Workshop STATS 303 (section 1) For Statistics First Year PhD students only. Discussion of relevant topics in first year student courses, consultation with PhD advisor. 
Holmes, S., Walther, G.  20142015 Spring 
Tuesday Wednesday Thursday 12:00pm  12:50pm Sequoia Hall 200 
PhD First Year Student Workshop STATS 303 (section 1) For Statistics First Year PhD students only. Discussion of relevant topics in first year student courses, consultation with PhD advisor. 
Holmes, S., Walther, G.  20142015 Spring 
Tuesday Wednesday Thursday 12:00pm  12:50pm Sequoia Hall 200 
Methods for Applied Statistics: Unsupervised Learning STATS 306B (section 1) Unsupervised learning techniques in statistics, machine learning, and data mining. 
Tibshirani, R.  20142015 Spring 
Monday Wednesday 3:15pm  4:30pm Mitchb67 
Theory of Probability (MATH 230C) STATS 310C (section 1) Continuous time stochastic processes: martingales, Brownian motion, stationary independent increments, Markov jump processes and Gaussian processes. Invariance principle,... 
Chatterjee, S.  20142015 Spring 
Tuesday Thursday 9:30am  10:45am Sequoia Hall 200 
Modern Applied Statistics: Data Mining STATS 315B (section 1) Twopart sequence. New techniques for predictive and descriptive learning using ideas that bridge gaps among statistics, computer science, and artificial intelligence.... 
Friedman, J.  20142015 Spring 
Tuesday Thursday 2:15pm  3:30pm Gates B1 
Stochastic Processes STATS 317 (section 1) Semimartingales, stochastic integration, Ito's formula, Girsanov's theorem. Gaussian and related processes. Stationary/isotropic processes. Integral geometry and geometric... 
Taylor, J.  20142015 Spring 
Monday Wednesday 2:15pm  3:30pm 100101K 
Literature of Statistics STATS 319 (section 1) Literature study of topics in statistics and probability culminating in oral and written reports. May be repeated for credit. 
Romano, J.  20142015 Spring 
Wednesday 1:00pm  1:50pm 250108 
Modern Spectral Analysis STATS 333 (section 1) Traditional spectral analysis encompassed Fourier methods and their elaborations, under the assumption of a simple superposition of sinusoids, independent of time. This... 
Chui, C., Donoho, D.  20142015 Spring 
Wednesday 2:15pm  4:05pm 380381T 
Statistical and Machine Learning Methods for Genomics (BIO 268, BIOMEDIN 245, CS 373, GENE 245) STATS 345 (section 1) Introduction to statistical and computational methods for genomics. Sample topics include: expectation maximization, hidden Markov model, Markov chain Monte Carlo,... 
Kundaje, A., Pritchard, J., Tang, H.  20142015 Spring 
Monday Wednesday 10:30am  11:50am 
Topic: Monte Carlo STATS 362 (section 1) Random numbers and vectors: inversion, acceptancerejection, copulas. Variance reduction: antithetics, stratification, control variates, importance sampling. MCMC: Markov... 
Owen, A.  20142015 Spring 
Monday Wednesday 2:15pm  3:15pm Herrin T185 
A Course in Bayesian Statistics (STATS 270) STATS 370 (section 1) Advancedlevel Bayesian statistics. Topics: Discussion of the mathematical and theoretical foundation for Bayesian inferential procedures. Examination of the construction... 
Wong, W.  20142015 Spring 
Monday Wednesday 9:30am  10:45am 200107 
Consulting Workshop STATS 390 (section 1) Skills required of practicing statistical consultants, including exposure to statistical applications. Students participate as consultants in the department's dropin... 
Fithian, W.  20142015 Spring 
Friday 12:00pm  12:50pm Sequoia Hall 200 
Consulting Workshop STATS 390 (section 1) Skills required of practicing statistical consultants, including exposure to statistical applications. Students participate as consultants in the department's dropin... 
Fithian, W.  20142015 Spring 
Friday 12:00pm  12:50pm Sequoia Hall 200 