Courses

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
C 336 336 13
Class # Section Date And Times Location Units LIM/ENR/WAIT
24156 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 28/28/1
24157 LAB 2 MoWe 11:00am - 11:59am Internet/Online 4 28/28/1
24158 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 28/28/2
24159 LAB 2 MoWe 1:00pm - 1:59pm Internet/Online 4 28/28/2
24160 LAB 2 MoWe 2:00pm - 2:59pm Internet/Online 4 28/28/0
24161 LAB 2 MoWe 3:00pm - 3:59pm Internet/Online 4 28/28/1
24162 LAB 2 MoWe 4:00pm - 4:59pm Internet/Online 4 28/28/0
24163 LAB 2 MoWe 5:00pm - 5:59pm Internet/Online 4 28/28/0
24164 LAB 2 MoWe 6:00pm - 6:59pm Internet/Online 4 28/28/0
24153 LAB 2 MoWe 8:00am - 8:59am Internet/Online 4 28/28/4
24154 LAB 2 MoWe 9:00am - 9:59am Internet/Online 4 28/28/1
24155 LAB 2 MoWe 10:00am - 10:59am Internet/Online 4 28/28/1

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 420 411 9
Class # Section Date And Times Location Units LIM/ENR/WAIT
24166 LAB 20 MoWe 8:00am - 8:59am Internet/Online 4 28/28/1
24167 LAB 20 MoWe 9:00am - 9:59am Internet/Online 4 28/28/2
24168 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 28/28/0
24169 LAB 20 MoWe 10:00am - 10:59am Internet/Online 4 28/28/1
24170 LAB 20 MoWe 11:00am - 11:59am Internet/Online 4 28/28/2
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 28/28/0
24173 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 28/28/2
24174 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 28/28/0
24175 LAB 20 MoWe 2:00pm - 2:59pm Internet/Online 4 28/28/0
24176 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 28/28/0
24177 LAB 20 MoWe 4:00pm - 4:59pm Internet/Online 4 28/28/0
24178 LAB 20 MoWe 5:00pm - 5:59pm Internet/Online 4 28/28/0
24179 LAB 20 MoWe 6:00pm - 6:59pm Internet/Online 4 28/28/2
33802 LAB 20 MoWe 3:00pm - 3:59pm Internet/Online 4 28/20/0
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
C 150 150 11
Class # Section Date And Times Location Units LIM/ENR/WAIT
26920 LAB 20 TuTh 9:00am - 9:59am 4 25/25/2
26921 LAB 20 TuTh 10:00am - 10:59am 4 26/26/1
26922 LAB 20 TuTh 11:00am - 11:59am 4 25/25/1
26923 LAB 20 TuTh 1:00pm - 1:59pm 4 25/25/1
26924 LAB 20 TuTh 5:00pm - 5:59pm 4 25/24/5
26925 LAB 20 TuTh 6:00pm - 6:59pm 4 25/25/1

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 19 1

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 120 116 4
Class # Section Date And Times Location Units LIM/ENR/WAIT
26611 LAB 33 We 10:00am - 10:59am 1 40/40/1
26612 LAB 33 We 9:00am - 9:59am 1 0/0/0
26613 LAB 33 We 3:00pm - 3:59pm 1 40/40/3
26614 LAB 33 We 4:00pm - 4:59pm 1 40/36/0

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
C 120 120 10
Class # Section Date And Times Location Units LIM/ENR/WAIT
26617 LAB 33 Fr 4:00pm - 4:59pm 1 40/40/3
32688 LAB 33 Fr 10:00am - 10:59am 1 40/40/5
33087 LAB 33 Fr 3:00pm - 3:59pm 1 40/40/2

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 334 326 2

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
Status Limit Enrolled Waitlist
O 50 37 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25394 LAB 89 Mo 8:00am - 9:59am 4 3/3/0
25395 LAB 89 Mo 10:00am - 11:59am 4 25/16/0
25847 LAB 89 Mo 2:00pm - 3:59pm 4 25/17/0
25848 LAB 89 Mo 4:00pm - 5:59pm 4 1/1/0

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 57 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
33104 LAB 131 TuTh 2:00pm - 2:59pm Internet/Online 4 35/28/0
33105 LAB 131 TuTh 5:00pm - 5:59pm Internet/Online 4 35/29/0

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
C 180 180 3
Class # Section Date And Times Location Units LIM/ENR/WAIT
24187 LAB 133 We 1:00pm - 2:59pm 3 30/30/0
24188 LAB 133 We 2:00pm - 3:59pm 3 30/30/0
24189 LAB 133 We 4:00pm - 5:59pm 3 30/30/2
24190 LAB 133 Th 3:00pm - 4:59pm 3 30/30/0
24191 LAB 133 Th 2:00pm - 3:59pm 3 30/30/1
24186 LAB 133 We 10:00am - 11:59am 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 330 325 13

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 198 186 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24204 LAB 135 Fr 1:00pm - 2:59pm Internet/Online 4 33/31/0
24205 LAB 135 Fr 1:00pm - 2:59pm Internet/Online 4 33/31/0
24206 LAB 135 Fr 2:00pm - 3:59pm Internet/Online 4 33/30/0
24207 LAB 135 Fr 2:00pm - 3:59pm Internet/Online 4 33/31/0
24208 LAB 135 Fr 4:00pm - 5:59pm Internet/Online 4 33/30/0
24209 LAB 135 Fr 5:00pm - 6:59pm Internet/Online 4 33/33/0

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
C 330 330 35

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
Status Limit Enrolled Waitlist
O 122 121 0

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

Course Times
TuTh 2:00pm - 3:29pm
Course Location
Internet/Online
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)
Gaston Sanchez Trujillo
Status Limit Enrolled Waitlist
C 60 60 3
Class # Section Date And Times Location Units LIM/ENR/WAIT
24211 LAB 151 Fr 9:00am - 10:59am 4 0/0/0
24212 LAB 151 Fr 11:00am - 12:59pm 4 30/30/1
24785 LAB 151 Fr 1:00pm - 2:59pm 4 0/0/0
24786 LAB 151 Fr 3:00pm - 4:59pm 4 30/30/2

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
C 140 140 31
Class # Section Date And Times Location Units LIM/ENR/WAIT
24217 LAB 153 Fr 9:00am - 10:59am 4 35/35/8
24218 LAB 153 Fr 1:00pm - 2:59pm 4 35/35/10
24219 LAB 153 Fr 2:00pm - 3:59pm 4 35/35/7
24220 LAB 153 Fr 4:00pm - 5:59pm 4 35/35/6

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 54 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24222 LAB 154 Mo 9:00am - 10:59am 4 35/26/0
24223 LAB 154 Mo 11:00am - 12:59pm Wheeler 104 4 0/0/0
25849 LAB 154 Mo 1:00pm - 2:59pm 4 0/1/0
25850 LAB 154 Mo 3:00pm - 4:59pm 4 35/27/0

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
Status Limit Enrolled Waitlist
O 115 112 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
C 40 40 3
Class # Section Date And Times Location Units LIM/ENR/WAIT
25330 LAB 158 Mo 9:00am - 10:59am 4 20/20/3
25331 LAB 158 Mo 11:00am - 12:59pm 4 22/20/0

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 49 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31589 LAB 159 We 2:00pm - 3:59pm Internet/Online 4 27/25/0
31590 LAB 159 We 5:00pm - 6:59pm Internet/Online 4 27/24/0

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 13 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 9 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 40 40 33

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 21 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 12 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24234 LAB 215 Fr 10:00am - 11:59am Internet/Online 4 25/12/0

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 Physics Building 1 4 25/25/0
32884 LAB 222 Th 6:00pm - 6:59pm Physics Building 1 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 46 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
24237 LAB 230 We 2:30pm - 4:29pm Internet/Online 4 40/35/0
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 38 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31597 LAB 240 4 50/38/0

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
C 20 20 6
Class # Section Date And Times Location Units LIM/ENR/WAIT
24239 LAB 248 Fr 1:00pm - 2:59pm Internet/Online 4 20/20/6

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 12 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
31592 LAB 259 We 2:00pm - 3:59pm Internet/Online 4 10/7/0
31593 LAB 259 We 5:00pm - 6:59pm Internet/Online 4 8/5/0

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
C 25 25 4

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 6 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 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 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 16 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
26037 LAB 375 40/16/0

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 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
23719 LAB 20 MoWe 1:00pm - 1:59pm Internet/Online 4 26/23/0
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 131A 001 LEC 001 - Statistical Methods for Data Science

Course Times
MoWeFr 2:00pm - 2:59pm
Course Location
Internet/Online
Course Units
4
Course number
131A
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 60 48 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23674 LAB 131 TuTh 9:00am - 9:59am Evans 334 4 30/22/0
23965 LAB 131 TuTh 10:00am - 10:59am Evans 334 4 30/26/0

2020 Fall 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 150 148 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23776 LAB 133 3 0/0/0
23777 LAB 133 3 0/0/0
23778 LAB 133 3 0/0/0
23779 LAB 133 3 0/0/0
23782 LAB 133 We 11:00am - 12:59pm Internet/Online 3 44/44/0
23783 LAB 133 We 1:00pm - 2:59pm Internet/Online 3 40/30/0
23784 LAB 133 We 3:00pm - 4:59pm Internet/Online 3 40/35/0
23786 LAB 133 Th 9:00am - 10:59am Internet/Online 3 40/39/0
23787 LAB 133 3 0/0/0
23788 LAB 133 3 0/0/0

2020 Fall STAT 134 001 LEC 001 - Concepts of Probability

Course Times
MoWeFr 1:00pm - 1:59pm
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 300 277 0

2020 Fall STAT 135 001 LEC 001 - Concepts of Statistics

Course Times
TuTh 5:00pm - 6:29pm
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)
Yun S. Song
Status Limit Enrolled Waitlist
O 180 122 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23734 LAB 135 Fr 2:00pm - 2:59pm Internet/Online 4 30/24/0
23735 LAB 135 Fr 2:00pm - 2:59pm Internet/Online 4 30/17/0
23796 LAB 135 Fr 10:00am - 10:59am Internet/Online 4 30/19/0
23797 LAB 135 Fr 10:00am - 10:59am Internet/Online 4 30/21/0
24645 LAB 135 Fr 12:00pm - 12:59pm Internet/Online 4 30/21/0
24646 LAB 135 Fr 12:00pm - 12:59pm Internet/Online 4 30/20/0

2020 Fall STAT 140 001 LEC 001 - Probability for Data Science

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
Course Units
4
Course number
140
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 335 332 0

2020 Fall STAT 150 001 LEC 001 - Stochastic Processes

Course Times
MoWeFr 1:00pm - 1:59pm
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, Ella Veronika Hiesmayr
Status Limit Enrolled Waitlist
O 92 78 0

2020 Fall STAT 151A 001 LEC 001 - Linear Modelling: Theory and Applications

Course Times
TuTh 12:30pm - 1:59pm
Course Location
Internet/Online
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
O 100 64 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
23687 LAB 151 Fr 9:00am - 10:59am Internet/Online 4 35/31/0
23688 LAB 151 Fr 11:00am - 12:59pm Internet/Online 4 35/33/0
25344 LAB 151 Fr 1:00pm - 2:59pm Internet/Online 4 0/0/0
25345 LAB 151 Fr 3:00pm - 4:59pm Internet/Online 4 0/0/0

2020 Fall STAT 153 001 LEC 001 - Introduction to Time Series

Course Times
TuTh 3:30pm - 4:59pm
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 140 127 0
Class # Section Date And Times Location Units LIM/ENR/WAIT
25390 LAB 153 Fr 9:00am - 10:59am Internet/Online 4 35/31/0
25391 LAB 153 Fr 11:00am - 12:59pm Internet/Online 4 35/34/0
25392 LAB 153 Fr 1:00pm - 2:59pm Internet/Online 4 35/29/0
25393 LAB 153 Fr 3:00pm - 4:59pm Internet/Online 4 35/33/0