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# Current Courses

## Pages

Title | Instructor(s) | Quarter | Day, Time, Location |
---|---|---|---|

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... |
Wang, C. | 2014-2015 Winter |
Friday 9:00am - 9:50am Gates B12 |

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... |
Wang, C. | 2014-2015 Winter |
Friday 9:00am - 9:50am Gates B12 |

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 5) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... |
Bi, N. | 2014-2015 Winter |
Friday 9:00am - 9:50am Mitchb67 |

Mathematics in the Real World (MATH 16) STATS 90 (section 1) Introduction to non-calculus applications of mathematical ideas and principles in real-world problems. Topics include probability and counting, basic statistical concepts... |
Poulson, J. | 2014-2015 Spring |
Monday Wednesday Friday 9:00am - 9:50am 380-380W |

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) |
Thomas, E. | 2014-2015 Winter |
Monday Tuesday Wednesday Thursday Friday 9:00am - 9:50am 420-040 |

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) |
Thomas, E. | 2014-2015 Winter |
Monday Tuesday Wednesday Thursday Friday 9:00am - 9:50am 420-040 |

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) |
Bacallado, S., Mukherjee, R. | 2014-2015 Spring |
Monday Tuesday Wednesday Thursday Friday 10:00am - 10:50am 420-040 |

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 60) STATS 160 (section 1) |
Bacallado, S., Mukherjee, R. | 2014-2015 Spring |
Monday Tuesday Wednesday Thursday Friday 10:00am - 10:50am 420-040 |

Introduction to Applied Statistics STATS 191 (section 1) Statistical tools for modern data analysis. Topics include regression and prediction, elements of the analysis of variance, bootstrap, and cross-validation. Emphasis is on... |
Taylor, J. | 2014-2015 Winter |
Tuesday Thursday 2:15pm - 3:30pm 380-380C |

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. | 2014-2015 Spring |
Monday Wednesday 4:30pm - 5:45pm Hewlett Teaching Center 103 |

Introduction to Statistical Inference STATS 200 (section 1) Modern statistical concepts and procedures derived from a mathematical framework. Statistical inference, decision theory; point and interval estimation, tests of... |
Siegmund, D. | 2014-2015 Winter |
Monday Wednesday Friday 10:00am - 10:50am 200-002 |

Introduction to Statistical Inference STATS 200 (section 1) Modern statistical concepts and procedures derived from a mathematical framework. Statistical inference, decision theory; point and interval estimation, tests of... |
Siegmund, D. | 2014-2015 Winter |
Monday Wednesday Friday 10:00am - 10:50am 200-002 |

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. | 2014-2015 Spring |
Tuesday Thursday 10:15am - 11:30am 380-380F |

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. | 2014-2015 Spring |
Tuesday Thursday 10:15am - 11:30am 380-380F |

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 state-space... |
Donoho, D. | 2014-2015 Spring |
Tuesday Thursday 2:15pm - 3:30pm 380-380F |

Introduction to the Bootstrap STATS 208 (section 1) The bootstrap is a computer-based method for assigning measures of accuracy to statistical estimates. By substituting computation in place of mathematical formulas, it... |
Donoho, D. | 2014-2015 Spring |
Tuesday Thursday 9:00am - 10:15am 50-52H |

Statistical Methods for Group Comparisons and Causal Inference (EDUC 260X, HRP 239) STATS 209 (section 1) Critical examination of statistical methods in social science applications, especially for cause and effect determinations. Topics: path analysis, multilevel models,... |
Rogosa, D., Du, W. | 2014-2015 Winter |
Tuesday Thursday 12:35pm - 2:05pm Sequoia Hall 200 |

Meta-research: Appraising Research Findings, Bias, and Meta-analysis (HRP 206, MED 206) STATS 211 (section 1) Open to graduate, medical, and undergraduate students. Appraisal of the quality and credibility of research findings; evaluation of sources of bias. Meta-analysis as a... |
Ioannidis, J., Olkin, I. | 2014-2015 Winter |
Friday 9:00am - 11:50am Alway Building, Room M112 |

Introduction to Graphical Models (STATS 313) STATS 213 (section 1) Multivariate Normal Distribution and Inference, Wishart distributions, graph theory, probabilistic Markov models, pairwise and global Markov property, decomposable graph,... |
Rajaratnam, B. | 2014-2015 Winter |
Tuesday Thursday 2:15pm - 3:30pm Herrin T185 |

Introduction to Statistical Learning STATS 216 (section 1) Overview of supervised learning, with a focus on regression and classification methods. Syllabus includes: linear and polynomial regression, logistic regression and linear... |
Mackey, L., Achanta, R., Fan, Z., Gross, S., Markovic, J., Orenstein, P. | 2014-2015 Winter |
Monday Wednesday 12:50pm - 2:05pm Gates B1 |

Introduction to Statistical Learning STATS 216 (section 1) Overview of supervised learning, with a focus on regression and classification methods. Syllabus includes: linear and polynomial regression, logistic regression and linear... |
Mackey, L., Achanta, R., Fan, Z., Gross, S., Markovic, J., Orenstein, P. | 2014-2015 Winter |
Monday Wednesday 12:50pm - 2:05pm Gates B1 |

Introduction to Stochastic Processes STATS 217 (section 1) Discrete and continuous time Markov chains, poisson processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions... |
Khare, A. | 2014-2015 Winter |
Tuesday Thursday 9:30am - 10:45am 530-127 |

Introduction to Stochastic Processes STATS 217 (section 1) Discrete and continuous time Markov chains, poisson processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions... |
Khare, A. | 2014-2015 Winter |
Tuesday Thursday 9:30am - 10:45am 530-127 |

Introduction to Stochastic Processes STATS 218 (section 1) Renewal theory, Brownian motion, Gaussian processes, second order processes, martingales. |
Romano, J. | 2014-2015 Spring |
Tuesday Thursday 9:30am - 10:45am 320-220 |

Statistical Learning Theory (CS 229T) STATS 231 (section 1) (Same as STATS 231) How do we formalize what it means for an algorithm to learn from data? This course focuses on developing mathematical tools for answering this... |
Liang, P. | 2014-2015 Winter |
Monday Wednesday 9:30am - 10:45am 380-380W |

The Future of Finance (ECON 152, ECON 252, PUBLPOL 364) STATS 238 (section 1) If you are interested in a career in finance or that touches finance (legal, regulatory, corporate, public policy), this course will give you a useful perspective. We will... |
Beder, T. | 2014-2015 Winter |
Monday 2:15pm - 4:05pm 160-314 |

Mathematical and Computational Finance Seminar (CME 242) STATS 239 (section 1) |
Jain, K. | 2014-2015 Winter | |

Mathematical and Computational Finance Seminar (CME 242) STATS 239 (section 1) |
Jain, K. | 2014-2015 Spring |
Wednesday 4:15pm - 5:30pm 200-303 |

Financial Models and Statistical Methods in Active Risk Management (CME 243) STATS 243 (section 1) (SCPD students register for 243P.) Market risk and credit risk, credit markets. Back testing, stress testing and Monte Carlo methods. Logistic regression, generalized... |
Lai, T. | 2014-2015 Winter |
Friday 11:00am - 12:50pm Thornt102 |

Financial Models and Statistical Methods in Risk Management STATS 243P (section 1) For SCPD students; see STATS243. |
Lai, T. | 2014-2015 Winter |
Friday 11:00am - 12:50pm |

Quantitative Trading: Algorithms, Data, and Optimization STATS 244 (section 1) Statistical trading rules and performances evaluation. Active portfolio management and dynamic investment strategies. Data analytics and models of transactions data. Limit... |
Lai, T. | 2014-2015 Winter |
Monday 7:00pm - 9:00pm Sequoia Hall 200 |

Mathematical Finance (MATH 238) STATS 250 (section 1) Stochastic models of financial markets. Forward and futures contracts. European options and equivalent martingale measures. Hedging strategies and management of risk. Term... |
Papanicolaou, G. | 2014-2015 Winter |
Tuesday Thursday 2:15pm - 3:30pm 300-300 |

Workshop in Biostatistics (HRP 260B) STATS 260B (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. | 2014-2015 Winter |
Thursday 1:15pm - 3:05pm MSOBX303 |

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. | 2014-2015 Spring |
Thursday 1:15pm - 3:05pm MSOBX303 |

Intermediate Biostatistics: Analysis of Discrete Data (BIOMEDIN 233, HRP 261) STATS 261 (section 1) Methods for analyzing data from case-control and cross-sectional studies: the 2x2 table, chi-square test, Fisher's exact test, odds ratios, Mantel-Haenzel methods,... |
Sainani, K. | 2014-2015 Winter |
Monday Wednesday 11:30am - 1:00pm Li Ka Shing Center, room 130 |

Intermediate Biostatistics: Regression, Prediction, Survival Analysis (HRP 262) STATS 262 (section 1) Methods for analyzing longitudinal data. Topics include Kaplan-Meier methods, Cox regression, hazard ratios, time-dependent variables, longitudinal data structures,... |
Sainani, K. | 2014-2015 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 Kaplan-Meier methods, Cox regression, hazard ratios, time-dependent variables, longitudinal data structures,... |
Sainani, K. | 2014-2015 Spring |
Wednesday 3:15pm - 4:45pm Li Ka Shing Center, room 120 |

A Course in Bayesian Statistics (STATS 370) STATS 270 (section 1) Advanced-level Bayesian statistics. Topics: Discussion of the mathematical and theoretical foundation for Bayesian inferential procedures. Examination of the construction... |
Wong, W. | 2014-2015 Spring |
Monday Wednesday 9:30am - 10:45am 200-107 |

Paradigms for Computing with Data STATS 290 (section 1) Advanced programming and computing techniques to support projects in data analysis and related research. For Statistics graduate students and others whose research... |
Chambers, J., Narasimhan, B. | 2014-2015 Winter |
Monday Wednesday Friday 10:00am - 10:50am Gates B3 |

Theory of Statistics STATS 300B (section 1) Elementary decision theory; loss and risk functions, Bayes estimation; UMVU estimator, minimax estimators, shrinkage estimators. Hypothesis testing and confidence... |
Siegmund, D. | 2014-2015 Winter |
Tuesday Thursday 11:00am - 12:15pm Sequoia Hall 200 |

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. | 2014-2015 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. | 2014-2015 Winter |
Monday Wednesday 2:15pm - 3:30pm 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. | 2014-2015 Winter |
Monday Wednesday 2:15pm - 3:30pm 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. | 2014-2015 Spring |
Tuesday Wednesday Thursday 12:00pm - 12:50pm Sequoia Hall 200 |

PhD First Year Student Workshop STATS 303 (section 1) |
Holmes, S., Walther, G. | 2014-2015 Spring |
Tuesday Wednesday Thursday 12:00pm - 12:50pm Sequoia Hall 200 |

Methods for Applied Statistics STATS 306A (section 1) Regression modeling extended to categorical data. Logistic regression. Loglinear models. Generalized linear models. Discriminant analysis. Categorical data models from... |
Efron, B., Wager, S., Walsh, D. | 2014-2015 Winter |
Monday Wednesday Friday 1:15pm - 2:05pm 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. | 2014-2015 Spring |
Monday Wednesday 3:15pm - 4:30pm Mitchb67 |

Theory of Probability (MATH 230B) STATS 310B (section 1) Conditional expectations, discrete time martingales, stopping times, uniform integrability, applications to 0-1 laws, Radon-Nikodym Theorem, ruin problems, etc. Other... |
Dembo, A. | 2014-2015 Winter |
Monday Wednesday 9:30am - 10:45am Sequoia Hall 200 |

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. | 2014-2015 Spring |
Tuesday Thursday 9:30am - 10:45am Sequoia Hall 200 |

Statistical Methods in Neuroscience STATS 312 (section 1) The goal is to discuss statistical methods for neuroscience in their natural habitat: the research questions, measurement technologies and experiment designs used in... |
Benjamini, Y. | 2014-2015 Winter |
Tuesday Thursday 1:15pm - 2:30pm 540-108 |