Title  Instructor(s)  Quarter  Day, Time, Location 

Riding the Data Wave STATS 48N (section 1) Imagine collecting a bit of your saliva and sending it in to one of the personalized genomics company: for very little money you will get back information about hundreds... 
Sabatti, C., SUR, P.  20152016 Autumn 
Tuesday Thursday 9:00am  10:20am 5052H 
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... 
20152016 Autumn 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 420040 

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... 
20152016 Autumn 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 420040 

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 3) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
20152016 Autumn 
Friday 10:30am  11:20am Sequoia Hall 200 

Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 4) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Walther, G.  20152016 Autumn 
Friday 11:30am  12:20pm Sequoia Hall 200 
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 4) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
Walther, G.  20152016 Autumn 
Friday 11:30am  12:20pm Sequoia Hall 200 
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... 
20152016 Winter 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 420040 

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... 
20152016 Winter 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 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... 
20152016 Winter  
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... 
20152016 Winter  
Introduction to Statistical Methods: Precalculus (PSYCH 10, STATS 160) STATS 60 (section 3) Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of... 
20152016 Winter  
Statistical Methods in Engineering and the Physical Sciences STATS 110 (section 1) Introduction to statistics for engineers and physical scientists. Topics: descriptive statistics, probability, interval estimation, tests of hypotheses, nonparametric... 
Rajaratnam, B., Bhattacharya, B., Bi, N., Panigrahi, S.  20152016 Autumn 
Monday Tuesday Wednesday Thursday 11:30am  12:20pm Hewlett Teaching Center 201 
Statistical Methods in Engineering and the Physical Sciences STATS 110 (section 1) Introduction to statistics for engineers and physical scientists. Topics: descriptive statistics, probability, interval estimation, tests of hypotheses, nonparametric... 
Rajaratnam, B., Bhattacharya, B., Bi, N., Panigrahi, S.  20152016 Autumn 
Monday Tuesday Wednesday Thursday 11:30am  12:20pm Hewlett Teaching Center 201 
Theory of Probability STATS 116 (section 3) Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and... 
Huang, R.  20152016 Autumn 
Monday 9:30am  10:20am 380381U 
Theory of Probability STATS 116 (section 3) Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and... 
Huang, R.  20152016 Autumn 
Monday 9:30am  10:20am 380381U 
Theory of Probability STATS 116 (section 5) Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and... 
20152016 Autumn 
Tuesday 6:30pm  7:20pm 380381U 

Theory of Probability STATS 116 (section 5) Probability spaces as models for phenomena with statistical regularity. Discrete spaces (binomial, hypergeometric, Poisson). Continuous spaces (normal, exponential) and... 
20152016 Autumn 
Tuesday 6:30pm  7:20pm 380381U 

Biostatistics (BIO 141) STATS 141 (section 1) Introductory statistical methods for biological data: describing data (numerical and graphical summaries); introduction to probability; and statistical inference (... 
Mukherjee, R.  20152016 Autumn 
Tuesday Thursday 1:30pm  2:50pm Braunaud 
Biostatistics (BIO 141) STATS 141 (section 2) Introductory statistical methods for biological data: describing data (numerical and graphical summaries); introduction to probability; and statistical inference (... 
Basu, K., Fukuyama, J., Guan, L., Tian, X.  20152016 Autumn 
Friday 11:30am  12:20pm 200030 
Biostatistics (BIO 141) STATS 141 (section 3) Introductory statistical methods for biological data: describing data (numerical and graphical summaries); introduction to probability; and statistical inference (... 
Basu, K., Fukuyama, J., Guan, L., Tian, X.  20152016 Autumn 
Friday 2:30pm  3:20pm 60120 
Statistical Methods in Computational Genetics STATS 155 (section 1) The computational methods necessary for the construction and evaluation of sequence alignments and phylogenies built from molecular data and genetic data such as micro... 
Holmes, S.  20152016 Autumn 
12:00am  12:00am 
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... 
Walther, G.  20152016 Autumn 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 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... 
Walther, G.  20152016 Autumn 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 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... 
Thomas, E.  20152016 Winter 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 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... 
Thomas, E.  20152016 Winter 
Monday Tuesday Wednesday Thursday Friday 9:30am  10:20am 420040 
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 crossvalidation. Emphasis is on... 
Walther, G.  20152016 Winter 
Monday Wednesday Friday 10:30am  11:20am Herrin T175 
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 fall and spring. It is recommended for students who want to use R in statistics, science... 
Suo, X.  20152016 Autumn 
Tuesday Thursday 12:00pm  1:20pm 380380F 
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., Arthur, J., Bai, Y., Gao, K., Walsh, D.  20152016 Autumn 
Tuesday Thursday 9:00am  10:20am 260113 
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., Arthur, J., Bai, Y., Gao, K., Walsh, D.  20152016 Autumn 
Tuesday Thursday 9:00am  10:20am 260113 
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... 
Reid, S.  20152016 Winter 
Monday Wednesday Friday 10:30am  11:20am 200002 
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... 
Reid, S.  20152016 Winter 
Monday Wednesday Friday 10:30am  11:20am 200002 
Data Mining and Analysis STATS 202 (section 1) Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining.... 
Mackey, L., Erdogdu, M., Gorham, J., Lee, M., Orenstein, P., Zheng, C.  20152016 Autumn 
Monday Wednesday Friday 1:30pm  2:20pm NVIDIA Auditorium 
Data Mining and Analysis STATS 202 (section 1) Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining.... 
Mackey, L., Erdogdu, M., Gorham, J., Lee, M., Orenstein, P., Zheng, C.  20152016 Autumn 
Monday Wednesday Friday 1:30pm  2:20pm NVIDIA Auditorium 
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... 
Taylor, J.  20152016 Winter 
Tuesday Thursday 10:30am  11:50am 380380D 
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... 
Taylor, J.  20152016 Winter 
Tuesday Thursday 10:30am  11:50am 380380D 
Applied Multivariate Analysis STATS 206 (section 1) Introduction to the statistical analysis of several quantitative measurements on each observational unit. Emphasis is on concepts, computerintensive methods. Examples... 
Johnstone, I., Michael, H.  20152016 Autumn 
Monday Wednesday 3:00pm  4:20pm Sequoia Hall 200 
Statistical Methods for Group Comparisons and Causal Inference (EDUC 260A, HRP 239) STATS 209 (section 1) Critical examination of statistical methods in social science and life sciences applications, especially for cause and effect determinations. Topics: mediating and... 
Rogosa, D.  20152016 Winter 
Wednesday Friday 1:30pm  3:20pm Sequoia Hall 200 
Metaresearch: Appraising Research Findings, Bias, and Metaanalysis (CHPR 206, 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. Metaanalysis as a... 
Ioannidis, J.  20152016 Winter 
Friday 9:30am  12:20pm Green Earth Sciences150 
Statistical Models in Biology STATS 215 (section 1) Poisson and renewal processes, Markov chains in discrete and continuous time, branching processes, diffusion. Applications to models of nucleotide evolution, recombination... 
Siegmund, D.  20152016 Winter 
Tuesday Thursday 1:30pm  2:50pm 380380F 
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.  20152016 Winter 
Monday Wednesday 1:30pm  2:50pm 
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.  20152016 Winter 
Monday Wednesday 1:30pm  2:50pm 
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... 
Feldheim, O.  20152016 Winter 
Monday Wednesday Friday 9:30am  10:20am Mitchb67 
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... 
Feldheim, O.  20152016 Winter 
Monday Wednesday Friday 9:30am  10:20am Mitchb67 
Stochastic Processes (MATH 136) STATS 219 (section 1) Introduction to measure theory, Lp spaces and Hilbert spaces. Random variables, expectation, conditional expectation, conditional distribution. Uniform integrability,... 
Zheng, T., Jafarov, J.  20152016 Autumn 
Monday Wednesday Friday 10:30am  11:20am 380380D 
Statistical Methods for Longitudinal Research (EDUC 351A) STATS 222 (section 1) Research designs and statistical procedures for timeordered (repeatedmeasures) data. The analysis of longitudinal panel data is central to empirical research on learning... 
Rogosa, D.  20152016 Autumn 
Thursday 3:00pm  5:50pm Sequoia Hall 200 
Machine Learning (CS 229) STATS 229 (section 1) Topics: statistical pattern recognition, linear and nonlinear regression, nonparametric methods, exponential family, GLMs, support vector machines, kernel methods, model... 
Ng, A., Ahluwalia, V., Ahres, Y., AlbanHidalgo, M., Anenberg, B., Bahtchevanov, I., CHU, H., CorbettDavies, S., Du, Y., Haque, A., How, P., Ishfaq, H., Iyer, K., Jiang, X., Kaplow, I., Lim, D., Lin, Y., Martinez, A., McCann, B., Parthasarathy, N., Qin, J., Sun, Y., Vyas, S., Wang, H., Zhou, L.  20152016 Autumn 
Monday Wednesday 9:30am  10:50am NVIDIA Auditorium 
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.  20152016 Winter 
Monday Wednesday 3:00pm  4:20pm Thornt110 
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 (computational science, economics, public policy, legal, regulatory, corporate, other), this course... 
Beder, T.  20152016 Winter 
Monday 11:30am  1:20pm School of Education 206 
Mathematical and Computational Finance Seminar (CME 242) STATS 239 (section 1) 
Jain, K.  20152016 Autumn 
Thursday 4:30pm  5:50pm School of Education 334 
Statistical Methods in Finance STATS 240 (section 1) (SCPD students register for 240P.) Regression analysis and applications to investment models. Principal components and multivariate analysis. Likelihood inference and... 
Lai, T., Jiang, B., Kuang, Y.  20152016 Autumn 
Friday 10:30am  12:20pm Gates B3 