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Current Courses

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)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of...

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)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of...

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)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of...

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)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of...

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)

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
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

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