Courses

2021 Fall STAT 2 001 LEC 001 - Introduction to Statistics

Course Times
MoWe 5:00pm - 6:29pm
Course Location
Internet/Online
Course Units
4
Course number
2
Course description

Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

Instructor(s)
Cari Kaufman
Status Limit Enrolled Waitlist
O 368 367 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23399 LAB 2 TuTh 4:00pm - 4:59pm Wheeler 104 4 26/26/0
23400 LAB 2 TuTh 6:00pm - 6:59pm Internet/Online 4 28/27/0
23401 LAB 2 TuTh 5:00pm - 5:59pm Etcheverry 3105 4 26/26/0
33570 LAB 2 TuTh 12:00pm - 12:59pm Evans 330 4 25/25/0
33571 LAB 2 TuTh 1:00pm - 1:59pm Evans 330 4 26/24/0
23331 LAB 2 TuTh 1:00pm - 1:59pm Evans 332 4 26/26/0
23332 LAB 2 TuTh 2:00pm - 2:59pm Evans 342 4 28/28/0
23333 LAB 2 TuTh 2:00pm - 2:59pm Evans 3 4 28/27/0
23334 LAB 2 TuTh 3:00pm - 3:59pm Evans 342 4 27/27/0
23335 LAB 2 TuTh 8:00am - 8:59am Internet/Online 4 26/26/0
23347 LAB 2 TuTh 1:00pm - 1:59pm Social Sciences Building 174 4 26/26/0
23402 LAB 2 TuTh 9:00am - 9:59am Evans 332 4 27/27/0
23403 LAB 2 TuTh 10:00am - 10:59am Evans 332 4 26/26/0
23404 LAB 2 TuTh 11:00am - 11:59am Evans 332 4 26/26/0

2021 Fall STAT C8 001 LEC 001 - Foundations of Data Science

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C8
Course description

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Instructor(s)
Anindita Adhikari, David Wagner
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26229 LAB 8 4 0/0/0

2021 Fall STAT C8 002 LEC 002 - Foundations of Data Science

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Stanley 105
Course Units
4
Course number
C8
Course description

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Instructor(s)
Anindita Adhikari, David Wagner
Status Limit Enrolled Waitlist
O 1 0 0

2021 Fall STAT 20 001 LEC 001 - Introduction to Probability and Statistics

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Shobhana Murali Stoyanov
Status Limit Enrolled Waitlist
O 705 698 1
Class # Section Date And Times Location Units LIM/ENR/WAIT
23361 LAB 20 MoWe 10:00am - 10:59am Wheeler 106 4 25/25/0
32523 LAB 20 MoWe 9:00am - 9:59am Evans 87 4 25/22/0
32524 LAB 20 MoWe 9:00am - 9:59am Evans 81 4 25/24/0
33635 LAB 20 MoWe 8:00am - 8:59am Internet/Online 4 28/28/0
33636 LAB 20 MoWe 4:00pm - 4:59pm Evans 344 4 25/23/0
23353 LAB 20 MoWe 1:00pm - 1:59pm Valley Life Sciences 2038 4 25/25/0
23338 LAB 20 MoWe 1:00pm - 1:59pm Evans 2 4 25/23/0
23339 LAB 20 MoWe 2:00pm - 2:59pm Evans 71 4 25/24/0
23340 LAB 20 MoWe 2:00pm - 2:59pm Evans 6 4 26/25/0
23341 LAB 20 MoWe 2:00pm - 2:59pm Evans 344 4 27/27/0
23342 LAB 20 MoWe 3:00pm - 3:59pm Evans 81 4 25/25/0
23343 LAB 20 Mo 3:00pm - 3:59pm Evans 340 4 25/24/0
23358 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 25/28/1
23359 LAB 20 MoWe 9:00am - 9:59am Evans 4 4 25/26/0
23360 LAB 20 MoWe 10:00am - 10:59am Physics Building 385 4 25/25/0
23362 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 23/19/0
23363 LAB 20 MoWe 11:00am - 11:59am Evans 332 4 25/25/0
23364 LAB 20 MoWe 12:00pm - 12:59pm Evans 2 4 25/25/0
23365 LAB 20 MoWe 12:00pm - 12:59pm Evans 332 4 25/25/0
23366 LAB 20 MoWe 1:00pm - 1:59pm Evans 344 4 25/25/0
32525 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 25/28/0
32526 LAB 20 MoWe 10:00am - 10:59am Evans 4 4 25/22/0
32527 LAB 20 MoWe 11:00am - 11:59am Etcheverry 3109 4 25/27/0
32528 LAB 20 MoWe 11:00am - 11:59am Evans 2 4 25/25/0
32529 LAB 20 MoWe 6:00pm - 6:59pm Internet/Online 4 26/24/0
32530 LAB 20 MoWe 5:00pm - 5:59pm Internet/Online 4 25/27/0
32531 LAB 20 MoWe 6:00pm - 6:59pm Internet/Online 4 26/26/0
32532 LAB 20 MoWe 3:00pm - 3:59pm Evans 344 4 26/26/0

2021 Fall STAT 20 002 LEC 002 - Introduction to Probability and Statistics

Course Times
MoWeFr 11:00am - 11:59am
Course Location
Evans 10
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Andrew Paul Bray
Status Limit Enrolled Waitlist
C 167 167 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24210 LAB 20 TuTh 3:00pm - 3:59pm Internet/Online 4 0/0/0
24211 LAB 20 TuTh 3:00pm - 3:59pm 4 0/0/0
24212 LAB 20 TuTh 4:00pm - 4:59pm Internet/Online 4 0/0/0
24213 LAB 20 TuTh 5:00pm - 5:59pm 4 0/0/0
24161 LAB 20 TuTh 12:00pm - 12:59pm Internet/Online 4 0/0/0
24162 LAB 20 TuTh 1:00pm - 1:59pm Internet/Online 4 0/0/0
24163 LAB 20 TuTh 1:00pm - 1:59pm Internet/Online 4 0/0/0
23350 LAB 20 TuTh 10:00am - 10:59am Evans 342 4 25/28/0
23351 LAB 20 TuTh 10:00am - 10:59am Evans 344 4 28/27/0
23352 LAB 20 TuTh 11:00am - 11:59am Evans 342 4 25/28/0
23336 LAB 20 TuTh 11:00am - 11:59am Evans 330 4 25/28/0
23348 LAB 20 TuTh 8:00am - 8:59am Evans 340 4 25/28/0
23349 LAB 20 TuTh 9:00am - 9:59am Evans 340 4 25/28/0
25245 LAB 20 TuTh 4:00pm - 4:59pm 4 0/0/0
32124 LAB 20 TuTh 2:00pm - 2:59pm 4 0/0/0
32125 LAB 20 TuTh 2:00pm - 2:59pm 4 0/0/0

2021 Fall STAT 33A 001 LEC 001 - Introduction to Programming in R

Course Times
Tu 2:00pm - 2:59pm
Course Location
Cory 277
Course Units
1
Course number
33A
Course description

An introduction to the R statistical software for students with minimal prior experience with programming. This course prepares students for data analysis with R. The focus is on the computational model that underlies the R language with the goal of providing a foundation for coding. Topics include data types and structures, such as vectors, data frames and lists; the REPL evaluation model; function calls, argument matching, and environments; writing simple functions and control flow. Tools for reading, analyzing, and plotting data are covered, such as data input/output, reshaping data, the formula language, and graphics models.

Instructor(s)
Gaston Sanchez Trujillo
Status Limit Enrolled Waitlist
O 100 81 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25273 LAB 33 Fr 9:00am - 9:59am Evans 342 1 25/18/0
25274 LAB 33 Fr 10:00am - 10:59am Evans 342 1 25/21/0
25275 LAB 33 Fr 1:00pm - 1:59pm Evans 342 1 25/22/0
25276 LAB 33 Fr 2:00pm - 2:59pm Evans 342 1 25/20/0

2021 Fall STAT 33B 001 LEC 001 - Introduction to Advanced Programming in R

Course Times
Th 2:00pm - 2:59pm
Course Location
Evans 60
Course Units
1
Course number
33B
Course description

The course is designed primarily for those who are already familiar with programming in another language, such as python, and want to understand how R works, and for those who already know the basics of R programming and want to gain a more in-depth understanding of the language in order to improve their coding. The focus is on the underlying paradigms in R, such as functional programming, atomic vectors, complex data structures, environments, and object systems. The goal of this course is to better understand programming principles in general and to write better R code that capitalizes on the language's design.

Instructor(s)
Gaston Sanchez Trujillo
Status Limit Enrolled Waitlist
O 100 80 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25278 LAB 33 Fr 11:00am - 11:59am Evans 342 1 25/24/0
25977 LAB 33 Fr 12:00pm - 12:59pm Evans 342 1 25/20/0
32662 LAB 33 Fr 3:00pm - 3:59pm Evans 342 1 25/19/0
32663 LAB 33 Fr 4:00pm - 4:59pm Evans 342 1 25/17/0

2021 Fall STAT 88 002 LEC 002 - Probability and Mathematical Statistics in Data Science

Course Units
3
Course number
88
Course description

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.

Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 88 001 LEC 001 - Probability and Mathematical Statistics in Data Science

Course Times
MoWeFr 1:00pm - 1:59pm
Course Location
Internet/Online
Course Units
3
Course number
88
Course description

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.

Instructor(s)
Anthony Cyril Donoghue, Meghana Kumar, Anton Edel Bobrov, Christopher Bledsoe Tice-Raskin
Status Limit Enrolled Waitlist
O 261 256 0

2021 Fall STAT C100 001 LEC 001 - Principles & Techniques of Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C100
Course description

In this course, students will explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction​, and decision-making.​ This class will focus on quantitative critical thinking​ and key principles and techniques needed to carry out this cycle. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.

Instructor(s)
Fernando Perez, Alvin Wan
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26409 LAB 100 4 1/0/0
26410 LAB 100 4 1/0/0

2021 Fall STAT C102 001 LEC 001 - Data, Inference, and Decisions

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
C102
Course description

This course develops the probabilistic foundations of inference in data science, and builds a comprehensive view of the modeling and decision-making life cycle in data science including its human, social, and ethical implications. Topics include: frequentist and Bayesian decision-making, permutation testing, false discovery rate, probabilistic interpretations of models, Bayesian hierarchical models, basics of experimental design, confidence intervals, causal inference, Thompson sampling, optimal control, Q-learning, differential privacy, clustering algorithms, recommendation systems and an introduction to machine learning tools including decision trees, neural networks and ensemble methods.

Instructor(s)
Ramesh Sridharan, Jacob Noah Steinhardt
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26311 LAB 102 Mo 9:00am - 9:59am Hearst Field Annex B5 4 0/0/0
26313 LAB 102 Mo 10:00am - 10:59am 4 0/0/0
26315 LAB 102 Mo 11:00am - 11:59am 4 0/0/0
26317 LAB 102 Mo 12:00pm - 12:59pm Hearst Field Annex B5 4 0/0/0
26473 LAB 102 Mo 4:00pm - 4:59pm Etcheverry 3113 4 0/0/0
26475 LAB 102 Mo 4:00pm - 4:59pm Etcheverry 3111 4 0/0/0
26477 LAB 102 Mo 3:00pm - 3:59pm Dwinelle 229 4 0/0/0
26471 LAB 102 Mo 1:00pm - 1:59pm Etcheverry 3108 4 0/0/0
32489 LAB 102 MoWe 5:00pm - 5:59pm Evans 334 4 0/0/0

2021 Fall STAT C131A 001 LEC 001 - Statistical Methods for Data Science

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Barker 101
Course Units
4
Course number
C131A
Course description

This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.

Instructor(s)
Shobhana Murali Stoyanov
Status Limit Enrolled Waitlist
O 70 60 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
30751 LAB 131 MoWe 1:00pm - 1:59pm Evans 332 4 35/34/0
30752 LAB 131 MoWe 3:00pm - 3:59pm Evans 332 4 35/26/0

2021 Fall STAT 133 001 LEC 001 - Concepts in Computing with Data

Course Times
MoWeFr 9:00am - 9:59am
Course Location
Evans 10
Course Units
3
Course number
133
Course description

An introduction to computationally intensive applied statistics. Topics will include organization and use of databases, visualization and graphics, statistical learning and data mining, model validation procedures, and the presentation of results.

Instructor(s)
Gaston Sanchez Trujillo
Status Limit Enrolled Waitlist
O 180 172 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23407 LAB 133 We 10:00am - 11:59am Evans 342 3 30/30/0
23408 LAB 133 We 12:00pm - 1:59pm Evans 342 3 30/29/0
23409 LAB 133 We 12:00pm - 1:59pm Wurster 101 3 30/25/0
23411 LAB 133 We 4:00pm - 5:59pm Evans 342 3 30/28/0
31044 LAB 133 We 10:00am - 11:59am Evans 340 3 30/30/0
31045 LAB 133 We 2:00pm - 3:59pm Evans 342 3 31/30/0

2021 Fall STAT 134 002 LEC 002 - Concepts of Probability

Course Units
4
Course number
134
Course description

An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.

Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 134 001 LEC 001 - Concepts of Probability

Course Times
MoWeFr 11:00am - 11:59am
Course Location
Internet/Online
Course Units
4
Course number
134
Course description

An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.

Instructor(s)
Adam R. Lucas
Status Limit Enrolled Waitlist
O 300 287 1

2021 Fall STAT 135 001 LEC 001 - Concepts of Statistics

Course Times
MoWeFr 1:00pm - 1:59pm
Course Location
Evans 10
Course Units
4
Course number
135
Course description

A comprehensive survey course in statistical theory and methodology. Topics include descriptive statistics, maximum likelihood estimation, non-parametric methods, introduction to optimality, goodness-of-fit tests, analysis of variance, bootstrap and computer-intensive methods and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.

Instructor(s)
Adam R. Lucas
Status Limit Enrolled Waitlist
O 180 143 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23367 LAB 135 Th 3:00pm - 4:59pm Evans 334 4 30/28/0
23368 LAB 135 Th 4:00pm - 5:59pm Evans 332 4 30/27/0
23418 LAB 135 Th 9:00am - 10:59am Evans 334 4 30/26/0
23419 LAB 135 Th 11:00am - 12:59pm Evans 334 4 30/19/0
24087 LAB 135 Th 1:00pm - 2:59pm Evans 334 4 30/23/0
24088 LAB 135 Th 2:00pm - 3:59pm Evans 332 4 30/20/0

2021 Fall STAT C140 001 LEC 001 - Probability for Data Science

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
C140
Course description

An introduction to probability, emphasizing the combined use of mathematics and programming to solve problems. Random variables, discrete and continuous families of distributions. Bounds and approximations. Dependence, conditioning, Bayes methods. Convergence, Markov chains. Least squares prediction. Random permutations, symmetry, order statistics. Use of numerical computation, graphics, simulation, and computer algebra.

Instructor(s)
Swupnil Kumar Sahai
Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 150 001 LEC 001 - Stochastic Processes

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Cory 277
Course Units
3
Course number
150
Course description

Random walks, discrete time Markov chains, Poisson processes. Further topics such as: continuous time Markov chains, queueing theory, point processes, branching processes, renewal theory, stationary processes, Gaussian processes.

Instructor(s)
Benson Au
Status Limit Enrolled Waitlist
O 100 62 0

2021 Fall STAT 151A 001 LEC 001 - Linear Modelling: Theory and Applications

Course Times
TuTh 11:00am - 12:29pm
Course Location
Valley Life Sciences 2060
Course Units
4
Course number
151A
Course description

A coordinated treatment of linear and generalized linear models and their application. Linear regression, analysis of variance and covariance, random effects, design and analysis of experiments, quality improvement, log-linear models for discrete multivariate data, model selection, robustness, graphical techniques, productive use of computers, in-depth case studies.

Instructor(s)
Samuel David Pimentel
Status Limit Enrolled Waitlist
C 79 79 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33580 LAB 151 Fr 1:00pm - 2:59pm Evans 334 4 0/0/0
33581 LAB 151 Fr 3:00pm - 4:59pm Evans 334 4 0/0/0
23321 LAB 151 Fr 10:00am - 11:59am Wheeler 204 4 39/39/0
23322 LAB 151 Fr 12:00pm - 1:59pm Wheeler 220 4 40/40/0

2021 Fall STAT 152 001 LEC 001 - Sampling Surveys

Course Units
4
Course number
152
Course description

Theory and practice of sampling from finite populations. Simple random, stratified, cluster, and double sampling. Sampling with unequal probabilities. Properties of various estimators including ratio, regression, and difference estimators. Error estimation for complex samples.

Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
32503 LAB 152 4 0/0/0
32504 LAB 152 4 0/0/0

2021 Fall STAT 153 001 LEC 001 - Introduction to Time Series

Course Times
We 3:00pm - 5:59pm
Course Location
Birge 50
Course Units
4
Course number
153
Course description

An introduction to time series analysis in the time domain and spectral domain. Topics will include: estimation of trends and seasonal effects, autoregressive moving average models, forecasting, indicators, harmonic analysis, spectra.

Instructor(s)
Ruoqi Yu
Status Limit Enrolled Waitlist
O 140 112 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24647 LAB 153 Fr 11:00am - 12:59pm Evans 332 4 35/33/0
24648 LAB 153 Fr 1:00pm - 2:59pm Evans 332 4 35/23/0
24649 LAB 153 Fr 3:00pm - 4:59pm Evans 332 4 35/30/0
24646 LAB 153 Fr 9:00am - 10:59am Evans 332 4 35/26/0

2021 Fall STAT 154 001 LEC 001 - Modern Statistical Prediction and Machine Learning

Course Times
TuTh 5:00pm - 6:29pm
Course Location
Moffitt Library 101
Course Units
4
Course number
154
Course description

Theory and practice of statistical prediction. Contemporary methods as extensions of classical methods. Topics: optimal prediction rules, the curse of dimensionality, empirical risk, linear regression and classification, basis expansions, regularization, splines, the bootstrap, model selection, classification and regression trees, boosting, support vector machines. Computational efficiency versus predictive performance. Emphasis on experience with real data and assessing statistical assumptions.

Instructor(s)
Song Mei
Status Limit Enrolled Waitlist
O 70 44 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23304 LAB 154 Mo 10:00am - 11:59am Moffitt Library 103 4 35/18/0
23305 LAB 154 Mo 2:00pm - 3:59pm Wheeler 220 4 35/26/0

2021 Fall STAT 155 001 LEC 001 - Game Theory

Course Units
3
Course number
155
Course description

General theory of zero-sum, two-person games, including games in extensive form and continuous games, and illustrated by detailed study of examples.

Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 156 001 LEC 001 - Causal Inference

Course Times
MoWe 5:00pm - 6:29pm
Course Location
Valley Life Sciences 2060
Course Units
4
Course number
156
Course description

This course will focus on approaches to causal inference using the potential outcomes framework. It will also use causal diagrams at an intuitive level. The main topics are classical randomized experiments, observational studies, instrumental variables, principal stratification and mediation analysis. Applications are drawn from a variety of fields including political science, economics, sociology, public health, and medicine. This course is a mix of statistical theory and data analysis. Students will be exposed to statistical questions that are relevant to decision and policy making.

Instructor(s)
Peng Ding
Status Limit Enrolled Waitlist
O 39 33 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26403 LAB 156 Fr 2:00pm - 3:59pm Wheeler 102 4 19/15/0
26404 LAB 156 Fr 4:00pm - 5:59pm Wheeler 130 4 20/18/0

2021 Fall STAT C200C 001 LEC 001 - Principles and Techniques of Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C200C
Course description

Explores the data science lifecycle: question formulation, data collection and cleaning, exploratory, analysis, visualization, statistical inference, prediction, and decision-making. Focuses on quantitative critical thinking and key principles and techniques: languages for transforming, querying and analyzing data; algorithms for machine learning methods: regression, classification and clustering; principles of informative visualization; measurement error and prediction; and techniques for scalable data processing. Research term project.

Instructor(s)
Fernando Perez, Alvin Wan
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26563 LAB 200 4 0/0/0

2021 Fall STAT 201A 001 LEC 001 - Introduction to Probability at an Advanced Level

Course Times
TuTh 9:30am - 10:59am
Course Location
Stanley 105
Course Units
4
Course number
201A
Course description

Distributions in probability and statistics, central limit theorem, Poisson processes, modes of convergence, transformations involving random variables.

Instructor(s)
Adityanand Guntuboyina
Status Limit Enrolled Waitlist
O 90 80 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33789 LAB 201 Mo 3:00pm - 4:59pm Evans 330 4 30/16/0
23314 LAB 201 Mo 12:00pm - 1:59pm Evans 334 4 35/35/0
23315 LAB 201 Mo 3:00pm - 4:59pm Evans 334 4 30/29/0

2021 Fall STAT 201B 001 LEC 001 - Introduction to Statistics at an Advanced Level

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Hearst Mining 390
Course Units
4
Course number
201B
Course description

Estimation, confidence intervals, hypothesis testing, linear models, large sample theory, categorical models, decision theory.

Instructor(s)
Haiyan Huang
Status Limit Enrolled Waitlist
O 90 74 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23317 LAB 201 We 11:00am - 12:59pm Evans 334 4 34/34/0
23318 LAB 201 We 1:00pm - 2:59pm Evans 334 4 30/29/0
33790 LAB 201 We 11:00am - 12:59pm Evans 344 4 30/11/0

2021 Fall STAT C205A 001 LEC 001 - Probability Theory

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Evans 344
Course Units
4
Course number
C205A
Course description

The course is designed as a sequence with Statistics C205B/Mathematics C218B with the following combined syllabus. Measure theory concepts needed for probability. Expection, distributions. Laws of large numbers and central limit theorems for independent random variables. Characteristic function methods. Conditional expectations, martingales and martingale convergence theorems. Markov chains. Stationary processes. Brownian motion.

Instructor(s)
Shirshendu Ganguly, Steven N Evans
Status Limit Enrolled Waitlist
O 30 18 0

2021 Fall STAT C206A 001 LEC 001 - Advanced Topics in Probability and Stochastic Process

Course Units
3
Course number
C206A
Course description

The topics of this course change each semester, and multiple sections may be offered. Advanced topics in probability offered according to students demand and faculty availability.

Status Limit Enrolled Waitlist
C 10 0 0

2021 Fall STAT 210A 001 LEC 001 - Theoretical Statistics

Course Times
TuTh 9:30am - 10:59am
Course Location
Valley Life Sciences 2060
Course Units
4
Course number
210A
Course description

An introduction to mathematical statistics, covering both frequentist and Bayesian aspects of modeling, inference, and decision-making. Topics include statistical decision theory; point estimation; minimax and admissibility; Bayesian methods; exponential families; hypothesis testing; confidence intervals; small and large sample theory; and M-estimation.

Instructor(s)
William Fithian
Status Limit Enrolled Waitlist
O 71 68 0

2021 Fall STAT 215A 001 LEC 001 - Statistical Models: Theory and Application

Course Times
TuTh 11:00am - 12:29pm
Course Location
Internet/Online
Course Units
4
Course number
215A
Course description

Applied statistics with a focus on critical thinking, reasoning skills, and techniques. Hands-on-experience with solving real data problems with high-level programming languages such as R. Emphasis on examining the assumptions behind standard statistical models and methods. Exploratory data analysis (e.g., graphical data summaries, PCAs, clustering analysis). Model formulation, fitting, and validation and testing. Linear regression and generalizations (e.g., GLMs, ridge regression, lasso).

Instructor(s)
Bin Yu
Status Limit Enrolled Waitlist
O 40 27 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23355 LAB 215 Fr 11:00am - 12:59pm Evans 334 4 40/27/0

2021 Fall STAT 243 001 LEC 001 - Introduction to Statistical Computing

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Physics Building 3
Course Units
4
Course number
243
Course description

Concepts in statistical programming and statistical computation, including programming principles, data and text manipulation, parallel processing, simulation, numerical linear algebra, and optimization.

Instructor(s)
Christopher Paciorek
Status Limit Enrolled Waitlist
O 72 63 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23433 LAB 243 Fr 12:00pm - 1:59pm Evans 344 4 37/37/0
23434 LAB 243 Fr 2:00pm - 3:59pm Evans 344 4 36/26/0
26729 LAB 243 4 0/0/0

2021 Fall STAT 251 001 LEC 001 - Stochastic Analysis with Applications to Mathematical Finance

Course Units
3
Course number
251
Course description

The essentials of stochastic analysis, particularly those most relevant to financial engineering, will be surveyed: Brownian motion, stochastic integrals, Ito's formula, representation of martingales, Girsanov's theorem, stochastic differential equations, and diffusion processes. Examples will be taken from the Black-Scholes-Merton theory of pricing and hedging contingent claims such as options, foreign market derivatives, and interest rate related contracts.

Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 256 001 LEC 001 - Causal Inference

Course Times
MoWe 5:00pm - 6:29pm
Course Location
Valley Life Sciences 2060
Course Units
4
Course number
256
Course description

This course will focus on approaches to causal inference using the potential outcomes framework. It will also use causal diagrams at an intuitive level. The main topics are classical randomized experiments, observational studies, instrumental variables, principal stratification and mediation analysis. Applications are drawn from a variety of fields including political science, economics, sociology, public health, and medicine. This course is a mix of statistical theory and data analysis. Students will be exposed to statistical questions that are relevant to decision and policy making.

Instructor(s)
Peng Ding
Status Limit Enrolled Waitlist
O 32 31 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26406 LAB 256 Fr 2:00pm - 3:59pm Wheeler 102 4 16/15/0
26407 LAB 256 Fr 4:00pm - 5:59pm Wheeler 130 4 16/16/0

2021 Fall STAT 260 001 LEC 001 - Topics in Probability and Statistics

Course Times
TuTh 3:30pm - 4:59pm
Course Location
Evans 344
Course Units
3
Course number
260
Course description

Special topics in probability and statistics offered according to student demand and faculty availability.

Instructor(s)
Giles Hooker
Status Limit Enrolled Waitlist
O 35 10 0

2021 Fall STAT 272 001 SES 001 - Statistical Consulting

Course Times
We 10:00am - 11:59am
Course Location
Evans 443
Course Units
3
Course number
272
Course description

To be taken concurrently with service as a consultant in the department's drop-in consulting service. Participants will work on problems arising in the service and will discuss general ways of handling such problems. There will be working sessions with researchers in substantive fields and occasional lectures on consulting.

Instructor(s)
Elizabeth Purdom
Status Limit Enrolled Waitlist
O 12 4 0

2021 Fall STAT 278B 001 SEM 001 - Statistics Research Seminar

Course Times
We 4:00pm - 4:59pm
Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
Song Mei
Status Limit Enrolled Waitlist
O 35 28 0

2021 Fall STAT 278B 002 SEM 002 - Statistics Research Seminar

Course Times
We 3:00pm - 3:59pm
Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
Alan Hammond
Status Limit Enrolled Waitlist
O 10 9 0

2021 Fall STAT 278B 004 SEM 004 - Statistics Research Seminar

Course Times
Tu 11:00am - 12:29pm
Course Location
Evans 1011
Course Units
4
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
George Shan
Status Limit Enrolled Waitlist
C 0 0 0

2021 Fall STAT 375 001 LEC 001 - Professional Preparation: Teaching of Probability and Statistics

Course Times
Mo 1:00pm - 2:59pm
Course Location
Evans 340
Course number
375
Course description

Discussion, problem review and development, guidance of laboratory classes, course development, supervised practice teaching.

Instructor(s)
Andrew Paul Bray
Status Limit Enrolled Waitlist
C 37 40 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23601 LAB 375 Mo 4:00pm - 4:59pm Social Sciences Building 126 37/40/0

2021 Fall STAT 375 002 LEC 002 - Professional Preparation: Teaching of Probability and Statistics

Course Times
Mo 1:00pm - 2:59pm
Course Location
Evans 330
Course number
375
Course description

Discussion, problem review and development, guidance of laboratory classes, course development, supervised practice teaching.

Instructor(s)
Andrew Paul Bray
Status Limit Enrolled Waitlist
O 20 13 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
34160 LAB 375 20/13/0

2021 Summer STAT 2 001 LEC 001 - Introduction to Statistics

Course Times
TuTh 9:30am - 11:29am
Course Location
Internet/Online
Course Units
4
Course number
2
Course description

Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

Instructor(s)
Anthony Cyril Donoghue
Status Limit Enrolled Waitlist
O 75 72 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
13838 LAB 2 TuTh 12:00pm - 1:29pm Internet/Online 4 38/37/0
13839 LAB 2 TuTh 2:00pm - 3:29pm Internet/Online 4 37/35/0

2021 Summer STAT 2 002 LEC 002 - Introduction to Statistics

Course Times
MoTuWeThFr 3:00pm - 4:29pm
Course Location
Internet/Online
Course Units
4
Course number
2
Course description

Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

Instructor(s)
Maureen Lahiff
Status Limit Enrolled Waitlist
O 80 62 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
13971 LAB 2 MoTuWeThFr 4:30pm - 5:29pm Internet/Online 4 31/31/0
13972 LAB 2 MoTuWeThFr 4:30pm - 5:29pm Internet/Online 4 31/31/0
13973 LAB 2 MoTuWeThFr 4:30pm - 5:29pm Internet/Online 4 20/0/0

2021 Summer STAT C8 001 LEC 001 - Foundations of Data Science

Course Times
MoTuWeThFr 10:00am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C8
Course description

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Instructor(s)
Katherine Tsai, Yanay Rosen
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
13911 LAB 8 4 0/0/0
13912 LAB 8 4 0/0/0
13958 LAB 8 4 0/0/0
13959 LAB 8 4 0/0/0
13960 LAB 8 4 0/0/0
13961 LAB 8 4 0/0/0
13993 LAB 8 4 0/0/0
13994 LAB 8 4 0/0/0
14457 LAB 8 4 0/0/0
14458 LAB 8 4 0/0/0
14459 LAB 8 4 0/0/0
14460 LAB 8 4 0/0/0
14461 LAB 8 4 0/0/0
15376 LAB 8 4 0/0/0
15377 LAB 8 4 0/0/0
15378 LAB 8 4 0/0/0

2021 Summer STAT 20 001 LEC 001 - Introduction to Probability and Statistics

Course Times
MoTuWeTh 11:00am - 12:29pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Fletcher H Ibser
Status Limit Enrolled Waitlist
O 140 96 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
13841 LAB 20 MoWeTh 1:00pm - 1:59pm Internet/Online 4 37/23/0
13842 LAB 20 MoWeTh 2:00pm - 2:59pm Internet/Online 4 34/25/0
14467 LAB 20 MoWeTh 5:00pm - 5:59pm Internet/Online 4 35/27/0
15963 LAB 20 MoWeTh 4:00pm - 4:59pm Internet/Online 4 34/21/0

2021 Summer STAT 88 001 LEC 001 - Probability and Mathematical Statistics in Data Science

Course Times
MoWeFr 6:00pm - 7:59pm
Course Location
Internet/Online
Course Units
3
Course number
88
Course description

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.

Instructor(s)
Zhiyi You
Status Limit Enrolled Waitlist
O 40 30 0

2021 Summer STAT C100 001 LEC 001 - Principles & Techniques of Data Science

Course Times
MoTuWeTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C100
Course description

In this course, students will explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction​, and decision-making.​ This class will focus on quantitative critical thinking​ and key principles and techniques needed to carry out this cycle. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.

Instructor(s)
Isaac A Schmidt, Raguvir Kunani
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
15450 LAB 100 4 0/0/0
14200 LAB 100 4 0/0/0
14202 LAB 100 4 0/0/0
14204 LAB 100 4 0/0/0
14205 LAB 100 4 0/0/0
14207 LAB 100 4 0/0/0
14370 LAB 100 4 0/0/0

2021 Summer STAT 134 001 LEC 001 - Concepts of Probability

Course Times
MoTuWeTh 1:00pm - 2:29pm
Course Location
Internet/Online
Course Units
4
Course number
134
Course description

An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.

Instructor(s)
Fletcher H Ibser
Status Limit Enrolled Waitlist
O 140 114 0

2021 Summer STAT 135 001 LEC 001 - Concepts of Statistics

Course Times
TuWeTh 9:00am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
135
Course description

A comprehensive survey course in statistical theory and methodology. Topics include descriptive statistics, maximum likelihood estimation, non-parametric methods, introduction to optimality, goodness-of-fit tests, analysis of variance, bootstrap and computer-intensive methods and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.

Instructor(s)
Likun Zhang
Status Limit Enrolled Waitlist
O 78 57 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
13850 LAB 135 TuTh 11:30am - 12:59pm 4 39/28/0
13851 LAB 135 TuTh 2:00pm - 3:29pm 4 39/29/0

2021 Summer STAT 155 001 LEC 001 - Game Theory

Course Times
TuWeTh 12:00pm - 1:59pm
Course Location
Internet/Online
Course Units
3
Course number
155
Course description

General theory of zero-sum, two-person games, including games in extensive form and continuous games, and illustrated by detailed study of examples.

Instructor(s)
Adam R. Lucas
Status Limit Enrolled Waitlist
O 100 32 0

2021 Spring STAT 2 001 LEC 001 - Introduction to Statistics

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
2
Course description

Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

Instructor(s)
Cari Kaufman
Status Limit Enrolled Waitlist
O 340 338 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24156 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 29/28/0
24157 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 28/28/0
24158 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 29/29/0
24159 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 29/29/0
24160 LAB 2 MoWe 2:00pm - 2:59pm Internet/Online 4 28/27/0
24164 LAB 2 MoWe 6:00pm - 6:59pm Internet/Online 4 28/27/0
24153 LAB 2 MoWe 8:00am - 8:59am Internet/Online 4 29/29/0
24154 LAB 2 MoWe 9:00am - 9:59am Internet/Online 4 29/29/0
24155 LAB 2 MoWe 10:00am - 10:59am Internet/Online 4 29/29/0

2021 Spring STAT C8 001 LEC 001 - Foundations of Data Science

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C8
Course description

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Instructor(s)
Babak Ayazifar, Swupnil Kumar Sahai
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24388 LAB 8 We 12:00pm - 1:59pm Etcheverry 3111 4 0/0/0
24389 LAB 8 We 12:00pm - 1:59pm Sutardja Dai 254 4 0/0/0
24390 LAB 8 We 12:00pm - 1:59pm Etcheverry 3113 4 0/0/0
24391 LAB 8 We 12:00pm - 1:59pm Cory 105 4 0/0/0
24392 LAB 8 We 2:00pm - 3:59pm Wheeler 150 4 0/0/0
24393 LAB 8 We 2:00pm - 3:59pm 4 0/0/0
24394 LAB 8 We 2:00pm - 3:59pm 4 0/0/0
24395 LAB 8 We 2:00pm - 3:59pm 4 0/0/0
24396 LAB 8 We 4:00pm - 5:59pm 4 0/0/0
24397 LAB 8 We 4:00pm - 5:59pm 4 0/0/0
24398 LAB 8 We 4:00pm - 5:59pm 4 0/0/0
24399 LAB 8 We 4:00pm - 5:59pm 4 0/0/0
24400 LAB 8 We 6:00pm - 7:59pm 4 0/0/0
24401 LAB 8 We 6:00pm - 7:59pm 4 0/0/0
24402 LAB 8 We 6:00pm - 7:59pm 4 0/0/0
24403 LAB 8 We 6:00pm - 7:59pm 4 0/0/0
24404 LAB 8 Th 8:00am - 9:59am 4 0/0/0
24405 LAB 8 Th 8:00am - 9:59am 4 0/0/0
24406 LAB 8 Th 8:00am - 9:59am 4 0/0/0
24407 LAB 8 Th 8:00am - 9:59am 4 0/0/0
24834 LAB 8 Th 10:00am - 11:59am 4 0/0/0
24835 LAB 8 Th 10:00am - 11:59am 4 0/0/0
24836 LAB 8 Th 10:00am - 11:59am 4 0/0/0
24837 LAB 8 Th 10:00am - 11:59am 4 0/0/0
25091 LAB 8 Th 12:00pm - 1:59pm 4 0/0/0
25133 LAB 8 Th 12:00pm - 1:59pm 4 0/0/0
25135 LAB 8 Th 12:00pm - 1:59pm 4 0/0/0
25136 LAB 8 Th 12:00pm - 1:59pm 4 0/0/0
25137 LAB 8 Th 2:00pm - 3:59pm 4 0/0/0
25138 LAB 8 Th 2:00pm - 3:59pm 4 0/0/0
25139 LAB 8 Th 2:00pm - 3:59pm 4 0/0/0
25140 LAB 8 Th 2:00pm - 3:59pm 4 0/0/0
25368 LAB 8 Th 4:00pm - 5:59pm 4 0/0/0
25369 LAB 8 Th 4:00pm - 5:59pm 4 0/0/0
25370 LAB 8 Th 4:00pm - 5:59pm 4 0/0/0
25371 LAB 8 Th 4:00pm - 5:59pm 4 0/0/0
25372 LAB 8 Th 6:00pm - 7:59pm 4 0/0/0
25373 LAB 8 Th 6:00pm - 7:59pm 4 0/0/0
25411 LAB 8 Th 6:00pm - 7:59pm 4 0/0/0
25883 LAB 8 Fr 12:00pm - 1:59pm 4 0/0/0
25884 LAB 8 Fr 2:00pm - 3:59pm 4 0/0/0
25885 LAB 8 Fr 12:00pm - 1:59pm 4 0/0/0
26004 LAB 8 Fr 2:00pm - 3:59pm 4 0/0/0
26005 LAB 8 Fr 12:00pm - 1:59pm 4 0/0/0
26006 LAB 8 Fr 12:00pm - 1:59pm 4 0/0/0
26007 LAB 8 Th 2:00pm - 3:59pm 4 0/0/0
26008 LAB 8 Fr 8:00am - 9:59am 4 0/0/0
26009 LAB 8 Fr 2:00pm - 3:59pm 4 0/0/0
26010 LAB 8 Fr 2:00pm - 3:59pm 4 0/0/0
26011 LAB 8 Fr 12:00pm - 1:59pm 4 0/0/0
27031 LAB 8 4 0/0/0

2021 Spring STAT 20 001 LEC 001 - Introduction to Probability and Statistics

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Fletcher H Ibser
Status Limit Enrolled Waitlist
O 420 387 1
Class # Section Date And Times Location Units LIM/ENR/WAIT
24166 LAB 20 MoWe 8:00am - 8:59am Internet/Online 4 28/28/0
24167 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 28/27/0
24168 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 28/27/0
24169 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 28/25/0
24170 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 28/24/1
24171 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 28/27/0
24172 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 28/26/0
24173 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 28/26/0
24174 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 28/25/0
24175 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 28/27/0
24176 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 28/25/0
24177 LAB 20 MoWe 4:00pm - 4:59pm Internet/Online 4 28/27/0
24178 LAB 20 MoWe 5:00pm - 5:59pm Internet/Online 4 28/25/0
24179 LAB 20 MoWe 6:00pm - 6:59pm Internet/Online 4 28/26/0
33802 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 28/22/0
33803 LAB 20 MoWe 12:00pm - 12:59pm Internet/Online 4 0/0/0

2021 Spring STAT 20 002 LEC 002 - Introduction to Probability and Statistics

Course Times
MoWeFr 1:00pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Adam R. Lucas
Status Limit Enrolled Waitlist
O 150 142 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26920 LAB 20 TuTh 9:00am - 9:59am Internet/Online 4 25/25/0
26921 LAB 20 TuTh 10:00am - 10:59am Internet/Online 4 25/23/0
26922 LAB 20 TuTh 11:00am - 11:59am Internet/Online 4 25/25/0
26923 LAB 20 TuTh 1:00pm - 1:59pm Internet/Online 4 25/22/0
26924 LAB 20 TuTh 5:00pm - 5:59pm Internet/Online 4 25/21/0
26925 LAB 20 TuTh 6:00pm - 6:59pm Internet/Online 4 26/26/0

2021 Spring STAT 24 001 SEM 001 - Freshman Seminars

Course Times
Mo 4:00pm - 4:59pm
Course Location
Internet/Online
Course Units
1
Course number
24
Course description

The Berkeley Seminar Program has been designed to provide new students with the opportunity to explore an intellectual topic with a faculty member in a small-seminar setting. Berkeley seminars are offered in all campus departments, and topics vary from department to department and semester to semester. Enrollment limited to 15 freshmen.

Instructor(s)
Deborah A Nolan
Status Limit Enrolled Waitlist
O 20 16 0

2021 Spring STAT 33A 001 LEC 001 - Introduction to Programming in R

Course Times
Mo 2:00pm - 2:59pm
Course Location
Internet/Online
Course Units
1
Course number
33A
Course description

An introduction to the R statistical software for students with minimal prior experience with programming. This course prepares students for data analysis with R. The focus is on the computational model that underlies the R language with the goal of providing a foundation for coding. Topics include data types and structures, such as vectors, data frames and lists; the REPL evaluation model; function calls, argument matching, and environments; writing simple functions and control flow. Tools for reading, analyzing, and plotting data are covered, such as data input/output, reshaping data, the formula language, and graphics models.

Instructor(s)
Deborah A Nolan
Status Limit Enrolled Waitlist
O 120 77 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26611 LAB 33 We 10:00am - 10:59am Internet/Online 1 40/29/0
26612 LAB 33 We 9:00am - 9:59am 1 0/0/0
26613 LAB 33 We 3:00pm - 3:59pm Internet/Online 1 40/27/0
26614 LAB 33 We 4:00pm - 4:59pm Internet/Online 1 40/21/0

2021 Spring STAT 33B 001 LEC 001 - Introduction to Advanced Programming in R

Course Times
We 2:00pm - 2:59pm
Course Location
Internet/Online
Course Units
1
Course number
33B
Course description

The course is designed primarily for those who are already familiar with programming in another language, such as python, and want to understand how R works, and for those who already know the basics of R programming and want to gain a more in-depth understanding of the language in order to improve their coding. The focus is on the underlying paradigms in R, such as functional programming, atomic vectors, complex data structures, environments, and object systems. The goal of this course is to better understand programming principles in general and to write better R code that capitalizes on the language's design.

Instructor(s)
Deborah A Nolan
Status Limit Enrolled Waitlist
O 120 107 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26617 LAB 33 Fr 4:00pm - 4:59pm Internet/Online 1 40/38/0
32688 LAB 33 Fr 10:00am - 10:59am Internet/Online 1 40/34/0
33087 LAB 33 Fr 3:00pm - 3:59pm Internet/Online 1 40/35/0

2021 Spring STAT 88 001 LEC 001 - Probability and Mathematical Statistics in Data Science

Course Times
MoWeFr 11:00am - 11:59am
Course Location
Internet/Online
Course Units
3
Course number
88
Course description

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.

Instructor(s)
Shobhana Murali Stoyanov
Status Limit Enrolled Waitlist
O 334 310 0

2021 Spring STAT 89A 001 LEC 001 - Linear Algebra for Data Science

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
89A
Course description

An introduction to linear algebra for data science. The course will cover introductory topics in linear algebra, starting with the basics; discrete probability and how prob- ability can be used to understand high-dimensional vector spaces; matrices and graphs as popular mathematical structures with which to model data (e.g., as models for term-document corpora, high-dimensional regression problems, ranking/classification of web data, adjacency properties of social network data, etc.); and geometric approaches to eigendecompositions, least-squares, principal components analysis, etc.

Instructor(s)
Michael William Mahoney, N. Benjamin Erichson
Status Limit Enrolled Waitlist
O 50 29 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25394 LAB 89 Mo 8:00am - 9:59am Internet/Online 4 2/1/0
25395 LAB 89 Mo 10:00am - 11:59am Internet/Online 4 25/16/0
25847 LAB 89 Mo 2:00pm - 3:59pm Internet/Online 4 25/11/0
25848 LAB 89 Mo 4:00pm - 5:59pm Internet/Online 4 1/1/0

2021 Spring STAT C100 001 LEC 001 - Principles & Techniques of Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C100
Course description

In this course, students will explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction​, and decision-making.​ This class will focus on quantitative critical thinking​ and key principles and techniques needed to carry out this cycle. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.

Instructor(s)
Andrew Paul Bray, Joseph Edgar Gonzalez
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
27161 LAB 100 We 8:00pm - 8:59pm 4 0/0/0
27163 LAB 100 We 8:00pm - 8:59pm 4 0/0/0
24820 LAB 100 Tu 4:00pm - 4:59pm 4 0/0/0
24821 LAB 100 Tu 4:00pm - 4:59pm 4 0/0/0
24822 LAB 100 We 10:00am - 10:59am 4 0/0/0
24823 LAB 100 We 10:00am - 10:59am 4 0/0/0
25116 LAB 100 We 11:00am - 11:59am 4 0/0/0
25117 LAB 100 We 11:00am - 11:59am 4 0/0/0
25118 LAB 100 Tu 11:00am - 11:59am 4 0/0/0
25119 LAB 100 Tu 11:00am - 11:59am 4 0/0/0
25120 LAB 100 Tu 11:00am - 11:59am 4 1/0/0
25121 LAB 100 Tu 11:00am - 11:59am 4 0/0/0
25122 LAB 100 Tu 12:00pm - 12:59pm 4 0/0/0
25123 LAB 100 Tu 12:00pm - 12:59pm 4 0/0/0
25124 LAB 100 Tu 12:00pm - 12:59pm 4 0/0/0
25125 LAB 100 Tu 12:00pm - 12:59pm 4 0/0/0
25126 LAB 100 Tu 1:00pm - 1:59pm 4 0/0/0
25127 LAB 100 Tu 1:00pm - 1:59pm 4 0/0/0
25128 LAB 100 Tu 1:00pm - 1:59pm 4 0/0/0
25129 LAB 100 Tu 1:00pm - 1:59pm 4 0/0/0
25130 LAB 100 Tu 2:00pm - 2:59pm 4 0/0/0
25131 LAB 100 Tu 2:00pm - 2:59pm 4 0/0/0
25132 LAB 100 Internet/Online 4 0/0/0
25930 LAB 100 Tu 2:00pm - 2:59pm 4 0/0/0
25932 LAB 100 Tu 2:00pm - 2:59pm 4 0/0/0
25934 LAB 100 Tu 3:00pm - 3:59pm 4 0/0/0
25936 LAB 100 Tu 3:00pm - 3:59pm 4 0/0/0
25938 LAB 100 Tu 3:00pm - 3:59pm 4 0/0/0
25940 LAB 100 Tu 3:00pm - 3:59pm 4 0/0/0
25942 LAB 100 Tu 4:00pm - 4:59pm 4 0/0/0
26079 LAB 100 Tu 4:00pm - 4:59pm 4 0/0/0
27139 LAB 100 We 9:00am - 9:59am 4 0/0/0
27141 LAB 100 We 10:00am - 10:59am 4 0/0/0
27143 LAB 100 We 11:00am - 11:59am 4 0/0/0
27145 LAB 100 We 9:00am - 9:59am 4 0/0/0
27147 LAB 100 Tu 5:00pm - 5:59pm 4 0/0/0
27149 LAB 100 Tu 6:00pm - 6:59pm 4 0/0/0
27151 LAB 100 Tu 7:00pm - 7:59pm 4 0/0/0
27153 LAB 100 Tu 7:00pm - 7:59pm 4 0/0/0
27155 LAB 100 Tu 7:00pm - 7:59pm 4 0/0/0
27157 LAB 100 Tu 7:00pm - 7:59pm 4 0/0/0
27159 LAB 100 We 8:00pm - 8:59pm 4 0/0/0

2021 Spring STAT C102 001 LEC 001 - Data, Inference, and Decisions

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C102
Course description

This course develops the probabilistic foundations of inference in data science, and builds a comprehensive view of the modeling and decision-making life cycle in data science including its human, social, and ethical implications. Topics include: frequentist and Bayesian decision-making, permutation testing, false discovery rate, probabilistic interpretations of models, Bayesian hierarchical models, basics of experimental design, confidence intervals, causal inference, Thompson sampling, optimal control, Q-learning, differential privacy, clustering algorithms, recommendation systems and an introduction to machine learning tools including decision trees, neural networks and ensemble methods.

Instructor(s)
Yan Shuo Tan, Ramesh Sridharan
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31341 LAB 102 4 0/0/0

2021 Spring STAT C131A 001 LEC 001 - Statistical Methods for Data Science

Course Times
MoWeFr 1:00pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
C131A
Course description

This course teaches a broad range of statistical methods that are used to solve data problems. Topics include group comparisons and ANOVA, standard parametric statistical models, multivariate data visualization, multiple linear regression, logistic regression and classification, regression trees and random forests. An important focus of the course is on statistical computing and reproducible statistical analysis. The course and lab include hands-on experience in analyzing real world data from the social, life, and physical sciences. The R statistical language is used.

Instructor(s)
Shobhana Murali Stoyanov
Status Limit Enrolled Waitlist
O 70 56 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33104 LAB 131 TuTh 2:00pm - 2:59pm Internet/Online 4 35/30/0
33105 LAB 131 TuTh 5:00pm - 5:59pm Internet/Online 4 35/26/0

2021 Spring STAT 133 001 LEC 001 - Concepts in Computing with Data

Course Times
MoWeFr 9:00am - 9:59am
Course Location
Internet/Online
Course Units
3
Course number
133
Course description

An introduction to computationally intensive applied statistics. Topics will include organization and use of databases, visualization and graphics, statistical learning and data mining, model validation procedures, and the presentation of results.

Instructor(s)
Gaston Sanchez Trujillo
Status Limit Enrolled Waitlist
O 180 176 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24187 LAB 133 We 1:00pm - 2:59pm Internet/Online 3 30/29/0
24188 LAB 133 We 2:00pm - 3:59pm Internet/Online 3 30/29/0
24189 LAB 133 We 4:00pm - 5:59pm Internet/Online 3 30/30/0
24190 LAB 133 Th 3:00pm - 4:59pm Internet/Online 3 30/30/0
24191 LAB 133 Th 2:00pm - 3:59pm Internet/Online 3 30/28/0
24186 LAB 133 We 10:00am - 11:59am Internet/Online 3 30/30/0

2021 Spring STAT 134 001 LEC 001 - Concepts of Probability

Course Times
MoWeFr 11:00am - 11:59am
Course Location
Internet/Online
Course Units
4
Course number
134
Course description

An introduction to probability, emphasizing concepts and applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Selected topics such as the Poisson process, Markov chains, characteristic functions.

Instructor(s)
Adam R. Lucas
Status Limit Enrolled Waitlist
O 339 331 0

2021 Spring STAT 135 001 LEC 001 - Concepts of Statistics

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
135
Course description

A comprehensive survey course in statistical theory and methodology. Topics include descriptive statistics, maximum likelihood estimation, non-parametric methods, introduction to optimality, goodness-of-fit tests, analysis of variance, bootstrap and computer-intensive methods and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.

Instructor(s)
Noureddine El Karoui
Status Limit Enrolled Waitlist
O 198 166 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24204 LAB 135 Fr 1:00pm - 2:59pm Internet/Online 4 34/31/0
24205 LAB 135 Fr 9:00am - 10:59am Internet/Online 4 33/19/0
24206 LAB 135 Fr 2:00pm - 3:59pm Internet/Online 4 33/31/0
24207 LAB 135 Fr 10:00am - 11:59am Internet/Online 4 33/24/0
24208 LAB 135 Fr 4:00pm - 5:59pm Internet/Online 4 33/32/0
24209 LAB 135 Fr 5:00pm - 6:59pm Internet/Online 4 34/29/0

2021 Spring STAT C140 001 LEC 001 - Probability for Data Science

Course Times
TuTh 11:00am - 12:29pm
Course Location
Internet/Online
Course Units
4
Course number
C140
Course description

An introduction to probability, emphasizing the combined use of mathematics and programming to solve problems. Random variables, discrete and continuous families of distributions. Bounds and approximations. Dependence, conditioning, Bayes methods. Convergence, Markov chains. Least squares prediction. Random permutations, symmetry, order statistics. Use of numerical computation, graphics, simulation, and computer algebra.

Instructor(s)
Anindita Adhikari
Status Limit Enrolled Waitlist
O 330 317 0

2021 Spring STAT 150 001 LEC 001 - Stochastic Processes

Course Times
MoWeFr 10:00am - 10:59am
Course Location
Internet/Online
Course Units
3
Course number
150
Course description

Random walks, discrete time Markov chains, Poisson processes. Further topics such as: continuous time Markov chains, queueing theory, point processes, branching processes, renewal theory, stationary processes, Gaussian processes.

Instructor(s)
Brett T Kolesnik, Mehdi Ouaki
Status Limit Enrolled Waitlist
O 123 110 0

2021 Spring STAT 153 001 LEC 001 - Introduction to Time Series

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
153
Course description

An introduction to time series analysis in the time domain and spectral domain. Topics will include: estimation of trends and seasonal effects, autoregressive moving average models, forecasting, indicators, harmonic analysis, spectra.

Instructor(s)
Jared D Fisher
Status Limit Enrolled Waitlist
O 170 157 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24217 LAB 153 Fr 9:00am - 10:59am Internet/Online 4 35/35/0
24218 LAB 153 Fr 1:00pm - 2:59pm Internet/Online 4 35/34/0
24219 LAB 153 Fr 2:00pm - 3:59pm Internet/Online 4 35/35/0
24220 LAB 153 Fr 4:00pm - 5:59pm Internet/Online 4 35/33/0
33903 LAB 153 Fr 8:00am - 9:59am Internet/Online 4 35/20/0

2021 Spring STAT 154 001 LEC 001 - Modern Statistical Prediction and Machine Learning

Course Times
TuTh 11:00am - 12:29pm
Course Location
Internet/Online
Course Units
4
Course number
154
Course description

Theory and practice of statistical prediction. Contemporary methods as extensions of classical methods. Topics: optimal prediction rules, the curse of dimensionality, empirical risk, linear regression and classification, basis expansions, regularization, splines, the bootstrap, model selection, classification and regression trees, boosting, support vector machines. Computational efficiency versus predictive performance. Emphasis on experience with real data and assessing statistical assumptions.

Instructor(s)
Noureddine El Karoui
Status Limit Enrolled Waitlist
O 70 45 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24222 LAB 154 Mo 9:00am - 10:59am Internet/Online 4 35/21/0
24223 LAB 154 Mo 11:00am - 12:59pm Wheeler 104 4 0/0/0
25849 LAB 154 Mo 1:00pm - 2:59pm 4 0/0/0
25850 LAB 154 Mo 3:00pm - 4:59pm Internet/Online 4 35/24/0

2021 Spring STAT 155 001 LEC 001 - Game Theory

Course Times
TuTh 5:00pm - 6:29pm
Course Location
Internet/Online
Course Units
3
Course number
155
Course description

General theory of zero-sum, two-person games, including games in extensive form and continuous games, and illustrated by detailed study of examples.

Instructor(s)
Shirshendu Ganguly, Adam Quinn Jaffe
Status Limit Enrolled Waitlist
O 115 99 0

2021 Spring STAT 157 001 SEM 001 - Seminar on Topics in Probability and Statistics

Course Units
3
Course number
157
Course description

Substantial student participation required. The topics to be covered each semester that the course may be offered will be announced by the middle of the preceding semester; see departmental bulletins. Recent topics include: Bayesian statistics, statistics and finance, random matrix theory, high-dimensional statistics.

Status Limit Enrolled Waitlist
C 1 0 0

2021 Spring STAT 158 001 LEC 001 - The Design and Analysis of Experiments

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
158
Course description

An introduction to the design and analysis of experiments. This course covers planning, conducting, and analyzing statistically designed experiments with an emphasis on hands-on experience. Standard designs studied include factorial designs, block designs, latin square designs, and repeated measures designs. Other topics covered include the principles of design, randomization, ANOVA, response surface methodoloy, and computer experiments.

Instructor(s)
Samuel David Pimentel
Status Limit Enrolled Waitlist
O 45 36 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25330 LAB 158 Mo 9:00am - 10:59am Internet/Online 4 23/17/0
25331 LAB 158 Mo 11:00am - 12:59pm Internet/Online 4 22/19/0

2021 Spring STAT 159 001 LEC 001 - Reproducible and Collaborative Statistical Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
159
Course description

A project-based introduction to statistical data analysis. Through case studies, computer laboratories, and a term project, students will learn practical techniques and tools for producing statistically sound and appropriate, reproducible, and verifiable computational answers to scientific questions. Course emphasizes version control, testing, process automation, code review, and collaborative programming. Software tools may include Bash, Git, Python, and LaTeX.

Instructor(s)
Philip Stark, Fernando Perez
Status Limit Enrolled Waitlist
O 56 42 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31589 LAB 159 We 2:00pm - 3:59pm Internet/Online 4 27/22/0
31590 LAB 159 We 5:00pm - 6:59pm Internet/Online 4 27/20/0

2021 Spring STAT C200C 001 LEC 001 - Principles and Techniques of Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C200C
Course description

Explores the data science lifecycle: question formulation, data collection and cleaning, exploratory, analysis, visualization, statistical inference, prediction, and decision-making. Focuses on quantitative critical thinking and key principles and techniques: languages for transforming, querying and analyzing data; algorithms for machine learning methods: regression, classification and clustering; principles of informative visualization; measurement error and prediction; and techniques for scalable data processing. Research term project.

Instructor(s)
Andrew Paul Bray, Joseph Edgar Gonzalez
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25945 LAB 200 Internet/Online 4 0/0/0

2021 Spring STAT C205B 001 LEC 001 - Probability Theory

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
C205B
Course description

The course is designed as a sequence with with Statistics C205A/Mathematics C218A with the following combined syllabus. Measure theory concepts needed for probability. Expection, distributions. Laws of large numbers and central limit theorems for independent random variables. Characteristic function methods. Conditional expectations, martingales and martingale convergence theorems. Markov chains. Stationary processes. Brownian motion.

Instructor(s)
James W Pitman
Status Limit Enrolled Waitlist
O 25 11 0

2021 Spring STAT C206B 001 LEC 001 - Advanced Topics in Probability and Stochastic Processes

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
3
Course number
C206B
Course description

The topics of this course change each semester, and multiple sections may be offered. Advanced topics in probability offered according to students demand and faculty availability.

Instructor(s)
Steven N Evans
Status Limit Enrolled Waitlist
O 30 6 0

2021 Spring STAT 210B 001 LEC 001 - Theoretical Statistics

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
210B
Course description

Introduction to modern theory of statistics; empirical processes, influence functions, M-estimation, U and V statistics and associated stochastic decompositions; non-parametric function estimation and associated minimax theory; semiparametric models; Monte Carlo methods and bootstrap methods; distributionfree and equivariant procedures; topics in machine learning. Topics covered may vary with instructor.

Instructor(s)
Martin J. Wainwright, Reese Pathak
Status Limit Enrolled Waitlist
C 41 35 6

2021 Spring STAT 212A 001 LEC 001 - Topics in Theoretical Statistics

Course Times
TuTh 11:00am - 12:29pm
Course Location
Internet/Online
Course Units
3
Course number
212A
Course description

This course introduces the student to topics of current research interest in theoretical statistics. Recent topics include information theory, multivariate analysis and random matrix theory, high-dimensional inference. Typical topics have been model selection; empirical and point processes; the bootstrap, stochastic search, and Monte Carlo integration; information theory and statistics; semi- and non-parametric modeling; time series and survival analysis.

Instructor(s)
Bin Yu
Status Limit Enrolled Waitlist
O 40 15 0

2021 Spring STAT 215B 001 LEC 001 - Statistical Models: Theory and Application

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
215B
Course description

Course builds on 215A in developing critical thinking skills and the techniques of advanced applied statistics. Particular topics vary with instructor. Examples of possible topics include planning and design of experiments, ANOVA and random effects models, splines, classification, spatial statistics, categorical data analysis, survival analysis, and multivariate analysis.

Instructor(s)
Elizabeth Purdom
Status Limit Enrolled Waitlist
O 25 8 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24234 LAB 215 Fr 10:00am - 11:59am Internet/Online 4 25/8/0

2021 Spring STAT 222 001 SEM 001 - Masters of Statistics Capstone Project

Course Times
Tu 5:00pm - 7:59pm
Course Location
Internet/Online
Course Units
4
Course number
222
Course description

The capstone project is part of the masters degree program in statistics. Students engage in professionally-oriented group research under the supervision of a research advisor. The research synthesizes the statistical, computational, economic, and social issues involved in solving complex real-world problems.

Instructor(s)
Thomas Bengtsson, Libor Pospisil
Status Limit Enrolled Waitlist
O 50 31 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25339 LAB 222 Th 5:00pm - 5:59pm Requested General Assignment 4 25/25/0
32884 LAB 222 Th 6:00pm - 6:59pm Requested General Assignment 4 25/6/0

2021 Spring STAT 230A 001 LEC 001 - Linear Models

Course Times
MoWe 5:00pm - 6:29pm
Course Location
Internet/Online
Course Units
4
Course number
230A
Course description

Theory of least squares estimation, interval estimation, and tests under the general linear fixed effects model with normally distributed errors. Large sample theory for non-normal linear models. Two and higher way layouts, residual analysis. Effects of departures from the underlying assumptions. Robust alternatives to least squares.

Instructor(s)
Peng Ding
Status Limit Enrolled Waitlist
O 50 45 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24237 LAB 230 We 2:30pm - 4:29pm Internet/Online 4 40/34/0
27228 LAB 230 Th 6:30pm - 8:29pm Internet/Online 4 12/11/0

2021 Spring STAT 240 001 LEC 001 - Nonparametric and Robust Methods

Course Times
TuTh 3:30pm - 4:59pm
Course Location
Internet/Online
Course Units
4
Course number
240
Course description

Standard nonparametric tests and confidence intervals for continuous and categorical data; nonparametric estimation of quantiles; robust estimation of location and scale parameters. Efficiency comparison with the classical procedures.

Instructor(s)
Jacob Noah Steinhardt
Status Limit Enrolled Waitlist
O 50 23 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31597 LAB 240 Internet/Online 4 50/23/0

2021 Spring STAT 248 001 LEC 001 - Analysis of Time Series

Course Times
TuTh 3:30pm - 4:59pm
Course Location
Internet/Online
Course Units
4
Course number
248
Course description

Frequency-based techniques of time series analysis, spectral theory, linear filters, estimation of spectra, estimation of transfer functions, design, system identification, vector-valued stationary processes, model building.

Instructor(s)
Adityanand Guntuboyina
Status Limit Enrolled Waitlist
O 24 20 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24239 LAB 248 Fr 1:00pm - 2:59pm Internet/Online 4 24/20/0

2021 Spring STAT 259 001 LEC 001 - Reproducible and Collaborative Statistical Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
259
Course description

A project-based introduction to statistical data analysis. Through case studies, computer laboratories, and a term project, students will learn practical techniques and tools for producing statistically sound and appropriate, reproducible, and verifiable computational answers to scientific questions. Course emphasizes version control, testing, process automation, code review, and collaborative programming. Software tools may include Bash, Git, Python, and LaTeX.

Instructor(s)
Philip Stark, Fernando Perez
Status Limit Enrolled Waitlist
O 20 7 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31592 LAB 259 We 2:00pm - 3:59pm Internet/Online 4 10/4/0
31593 LAB 259 We 5:00pm - 6:59pm Internet/Online 4 8/3/0

2021 Spring STAT 260 001 LEC 001 - Topics in Probability and Statistics

Course Times
MoWe 10:00am - 11:29am
Course Location
Internet/Online
Course Units
3
Course number
260
Course description

Special topics in probability and statistics offered according to student demand and faculty availability.

Instructor(s)
Song Mei
Status Limit Enrolled Waitlist
O 29 15 0

2021 Spring STAT 272 001 SES 001 - Statistical Consulting

Course Times
Mo 2:00pm - 3:59pm
Course Location
Internet/Online
Course Units
3
Course number
272
Course description

To be taken concurrently with service as a consultant in the department's drop-in consulting service. Participants will work on problems arising in the service and will discuss general ways of handling such problems. There will be working sessions with researchers in substantive fields and occasional lectures on consulting.

Instructor(s)
Jon Mcauliffe
Status Limit Enrolled Waitlist
O 12 8 0

2021 Spring STAT 278B 001 SEM 001 - Statistics Research Seminar

Course Times
We 4:00pm - 4:59pm
Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
Song Mei
Status Limit Enrolled Waitlist
O 30 14 0

2021 Spring STAT 278B 002 SEM 002 - Statistics Research Seminar

Course Times
We 3:00pm - 3:59pm
Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
Alan Hammond
Status Limit Enrolled Waitlist
O 15 7 0

2021 Spring STAT 278B 003 SEM 003 - Statistics Research Seminar

Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Status Limit Enrolled Waitlist
C 0 0 0

2021 Spring STAT 278B 004 SEM 004 - Statistics Research Seminar

Course Times
Tu 11:00am - 12:29pm
Course Location
Internet/Online
Course number
278B
Course description

Special topics, by means of lectures and informational conferences.

Instructor(s)
Lisa R. Goldberg
Status Limit Enrolled Waitlist
C 15 0 0

2021 Spring STAT 375 001 LEC 001 - Professional Preparation: Teaching of Probability and Statistics

Course Times
Fr 11:00am - 11:59am
Course Location
Internet/Online
Course number
375
Course description

Discussion, problem review and development, guidance of laboratory classes, course development, supervised practice teaching.

Instructor(s)
Fletcher H Ibser
Status Limit Enrolled Waitlist
O 30 18 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26037 LAB 375 Internet/Online 40/18/0

2020 Fall STAT 2 001 LEC 001 - Introduction to Statistics

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
2
Course description

Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

Instructor(s)
Cari Kaufman
Status Limit Enrolled Waitlist
C 311 308 2
Class # Section Date And Times Location Units LIM/ENR/WAIT
23697 LAB 2 MoWe 9:00am - 9:59am Internet/Online 4 26/26/0
23698 LAB 2 MoWe 10:00am - 10:59am Internet/Online 4 28/28/1
23699 LAB 2 MoWe 10:00am - 10:59am Internet/Online 4 25/24/0
23700 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 27/26/0
23701 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 24/24/0
23713 LAB 2 MoWe 9:00am - 9:59am Internet/Online 4 25/25/0
23770 LAB 2 MoWe 12:00pm - 12:59pm Internet/Online 4 29/28/1
23771 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 26/26/0
23772 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 25/25/0
23773 LAB 2 MoWe 2:00pm - 2:59pm Internet/Online 4 26/26/0
23774 LAB 2 MoWe 2:00pm - 2:59pm Internet/Online 4 25/24/0
23775 LAB 2 MoWe 3:00pm - 3:59pm Internet/Online 4 27/26/0

2020 Fall STAT C8 001 LEC 001 - Foundations of Data Science

Course Times
MoWeFr 11:00am - 11:59am
Course Location
Internet/Online
Course Units
4
Course number
C8
Course description

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Instructor(s)
David Wagner, Swupnil Kumar Sahai
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33193 LAB 8 Internet/Online 4 0/0/0

2020 Fall STAT 20 001 LEC 001 - Introduction to Probability and Statistics

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Fletcher H Ibser
Status Limit Enrolled Waitlist
O 400 385 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23704 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 26/21/0
23705 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 26/26/0
23706 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 26/25/0
23707 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 26/23/0
23708 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 26/23/0
23709 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 26/22/0
23725 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 26/26/0
23726 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 26/23/0
23727 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 27/26/0
23728 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 26/26/0
23729 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 26/26/1
23730 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 26/22/0
23731 LAB 20 MoWe 12:00pm - 12:59pm Internet/Online 4 26/24/0
23732 LAB 20 MoWe 12:00pm - 12:59pm Internet/Online 4 26/23/0
23733 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 26/26/0

2020 Fall STAT 20 002 LEC 002 - Introduction to Probability and Statistics

Course Times
MoWeFr 12:00pm - 12:59pm
Course Location
Internet/Online
Course Units
4
Course number
20
Course description

For students with mathematical background who wish to acquire basic concepts. Relative frequencies, discrete probability, random variables, expectation. Testing hypotheses. Estimation. Illustrations from various fields.

Instructor(s)
Shobhana Murali Stoyanov
Status Limit Enrolled Waitlist
O 349 342 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23702 LAB 20 TuTh 11:00am - 11:59am Internet/Online 4 40/25/0
23714 LAB 20 TuTh 8:00pm - 8:59pm Internet/Online 4 40/31/0
23715 LAB 20 TuTh 9:00am - 9:59am Internet/Online 4 40/28/0
23716 LAB 20 TuTh 10:00am - 10:59am Internet/Online 4 40/25/0
23717 LAB 20 TuTh 10:00am - 10:59am Internet/Online 4 40/21/1
23718 LAB 20 TuTh 11:00am - 11:59am Internet/Online 4 40/31/0
24732 LAB 20 TuTh 12:00pm - 12:59pm Internet/Online 4 40/22/1
24733 LAB 20 TuTh 1:00pm - 1:59pm Internet/Online 4 40/21/0
24734 LAB 20 TuTh 1:00pm - 1:59pm Internet/Online 4 40/29/0
24787 LAB 20 TuTh 2:00pm - 2:59pm Internet/Online 4 40/24/0
24788 LAB 20 TuTh 2:00pm - 2:59pm Internet/Online 4 40/21/0
24789 LAB 20 TuTh 3:00pm - 3:59pm Internet/Online 4 40/15/0
24790 LAB 20 TuTh 4:00pm - 4:59pm Internet/Online 4 40/23/0
26545 LAB 20 TuTh 4:00pm - 4:59pm Internet/Online 4 40/26/0

2020 Fall STAT 33A 001 LEC 001 - Introduction to Programming in R

Course Times
We 1:00pm - 1:59pm
Course Location
Internet/Online
Course Units
1
Course number
33A
Course description

An introduction to the R statistical software for students with minimal prior experience with programming. This course prepares students for data analysis with R. The focus is on the computational model that underlies the R language with the goal of providing a foundation for coding. Topics include data types and structures, such as vectors, data frames and lists; the REPL evaluation model; function calls, argument matching, and environments; writing simple functions and control flow. Tools for reading, analyzing, and plotting data are covered, such as data input/output, reshaping data, the formula language, and graphics models.

Instructor(s)
Nick Ulle
Status Limit Enrolled Waitlist
O 140 107 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26588 LAB 33 Fr 9:00am - 9:59am Internet/Online 1 35/26/0
26589 LAB 33 Fr 10:00am - 10:59am Internet/Online 1 35/30/0
26590 LAB 33 Fr 11:00am - 11:59am Internet/Online 1 35/25/0
26591 LAB 33 Fr 12:00pm - 12:59pm Internet/Online 1 35/26/0

2020 Fall STAT 33B 001 LEC 001 - Introduction to Advanced Programming in R

Course Times
We 3:00pm - 3:59pm
Course Location
Internet/Online
Course Units
1
Course number
33B
Course description

The course is designed primarily for those who are already familiar with programming in another language, such as python, and want to understand how R works, and for those who already know the basics of R programming and want to gain a more in-depth understanding of the language in order to improve their coding. The focus is on the underlying paradigms in R, such as functional programming, atomic vectors, complex data structures, environments, and object systems. The goal of this course is to better understand programming principles in general and to write better R code that capitalizes on the language's design.

Instructor(s)
Nick Ulle
Status Limit Enrolled Waitlist
O 120 103 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26593 LAB 33 Fr 2:00pm - 2:59pm Internet/Online 1 60/50/0
32191 LAB 33 Fr 3:00pm - 3:59pm Internet/Online 1 60/53/0

2020 Fall STAT 88 001 LEC 001 - Probability and Mathematical Statistics in Data Science

Course Times
MoWeFr 9:00am - 9:59am
Course Location
Internet/Online
Course Units
3
Course number
88
Course description

In this connector course we will state precisely and prove results discovered while exploring data in Data 8. Topics include: probability, conditioning, and independence; random variables; distributions and joint distributions; expectation, variance, tail bounds; Central Limit Theorem; symmetries in random permutations; prior and posterior distributions; probabilistic models; bias-variance tradeoff; testing hypotheses; correlation and the regression model.

Instructor(s)
Wooseok Ha, Jamarcus Liu, Daniel M Cohen, David Lyu
Status Limit Enrolled Waitlist
O 330 305 0

2020 Fall STAT C100 001 LEC 001 - Principles & Techniques of Data Science

Course Times
TuTh 9:30am - 10:59am
Course Location
Internet/Online
Course Units
4
Course number
C100
Course description

In this course, students will explore the data science lifecycle, including question formulation, data collection and cleaning, exploratory data analysis and visualization, statistical inference and prediction​, and decision-making.​ This class will focus on quantitative critical thinking​ and key principles and techniques needed to carry out this cycle. These include languages for transforming, querying and analyzing data; algorithms for machine learning methods including regression, classification and clustering; principles behind creating informative data visualizations; statistical concepts of measurement error and prediction; and techniques for scalable data processing.

Instructor(s)
Anthony D Joseph, Fernando Perez
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33503 LAB 100 Internet/Online 4 1/0/0
33504 LAB 100 Internet/Online 4 1/0/0

2020 Fall STAT C102 001 LEC 001 - Data, Inference, and Decisions

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
Course Units
4
Course number
C102
Course description

This course develops the probabilistic foundations of inference in data science, and builds a comprehensive view of the modeling and decision-making life cycle in data science including its human, social, and ethical implications. Topics include: frequentist and Bayesian decision-making, permutation testing, false discovery rate, probabilistic interpretations of models, Bayesian hierarchical models, basics of experimental design, confidence intervals, causal inference, Thompson sampling, optimal control, Q-learning, differential privacy, clustering algorithms, recommendation systems and an introduction to machine learning tools including decision trees, neural networks and ensemble methods.

Instructor(s)
Michael Jordan, Jacob Noah Steinhardt
Status Limit Enrolled Waitlist
C 0 0 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33307 LAB 102 Mo 9:00am - 9:59am Internet/Online 4 0/0/0
33309 LAB 102 Mo 10:00am - 10:59am Internet/Online 4 0/0/0
33311 LAB 102 Mo 11:00am - 11:59am Internet/Online 4 0/0/0
33313 LAB 102 Mo 12:00pm - 12:59pm Internet/Online 4 0/0/0
33567 LAB 102 Mo 1:00pm - 1:59pm Internet/Online 4 0/0/0
33569 LAB 102 Mo 2:00pm - 2:59pm Internet/Online 4 0/0/0
33573 LAB 102 Mo 4:00pm - 4:59pm Internet/Online 4 0/0/0