Course Listing for 2023-24Note:This is a TENTATIVE schedule. The course listings shown here are neither guaranteed, nor considered "final". Department Chairs may provide updated information regarding course offerings or faculty assignments throughout the year. Be sure to check this list regularly for new or revised information.

Course Title description Fall 2023 Winter 2024 Spring 2024 Summer 2024 STATS 005 STATS 5An introduction to the field of Data Science; intended for entering freshman and transfers. Babak Shahbaba

STATS 006 STATS 6Introduces the full data cycle. Topics include data collection and retrieval, data cleaning, exploratory analysis and visualization, introduction to statistical modeling, inference, and communicating findings. Applications include real data from a wide-range of fields with emphasis on understanding reproducible practices. Mine Dogucu

Mine Dogucu

STATS 007 STATS 7Lecture, three hours; discussion, one to two hours. Basic inferential statistics including confidence intervals and hypothesis testing on means and proportions, t-distribution, Chi Square, regression and correlation. F-distribution and nonparametric statistics included if time permits. Only one course from Statistics 7, Statistics 8, Management 7, or Biological Sciences 7 may be taken for credit. No credit for Statistics 7 if taken after Statistics 67. David S Armstrong (2)

Brigitte Baldi (2)

Brigitte Baldi (2)

Lee Ellen Kucera

David S Armstrong

Brigitte Baldi (2)

Lee Ellen Kucera (2)

STATS 008 STATS 8Lecture, three hours; discussion, one hour. Teaches introductory statistical techniques used to collect and analyze experimental and observational data for health sciences and molecular, cellular, environmental and evolutionary biology. Specific topics include exploration of data producing data, probability and sampling distributions, basic statistical inference for means, proportions, linear regression, and analysis of variance. Only one course from Statistics 8, Statistics 7, Management 7, Biological Sciences 7, or Social Ecology 13 may be taken for credit. Brigitte Baldi

Brigitte Baldi

Brigitte Baldi

STATS 067 STATS 67Lecture, three hours; discussion, two hours. Introduction to the basic concepts of probability and statistics with discussion of applications to computer science. David S Armstrong

Sevan Gregory Gulesserian

Mine Dogucu (2)

David S Armstrong (2)

Sevan Gregory Gulesserian

Stacy Morrow

Stacy Morrow (2)

David S Armstrong (2)

STATS 068 STATS 68Introduces key concepts in statistical computing. Techniques such as exploratory data analysis, data visualization, simulation, and optimization methods, will be presented in the context of data analysis within a statistical computing environment. David S Armstrong

STATS 110 STATS 110Lecture, three hours; laboratory, one hour. Introduction to statistical methods for analyzing data from experiments and surveys. Methods covered include two-sample procedures, analysis of variance, simple and multiple linear regression. Sevan Gregory Gulesserian (2)

STATS 111 STATS 111Lecture, three hours; laboratory, one hour. Introduction to statistical methods for analyzing data from surveys or experiments. Emphasizes application and understanding of methods for categorical data including contingency tables, logistic and Poisson regression, loglinear models. Concurrent with Statistics 202. Ana Kenney

STATS 112 STATS 112Lecture, three hours; laboratory, one hour. Introduction to statistical methods for analyzing longitudinal data from experiments and cohort studies. Topics covered include survival methods for censored time-to-event data, linear mixed models, non-linear mixed effects models, and generalized estimating equations. Concurrent with Statistics 203. Sevan Gregory Gulesserian

STATS 115 STATS 115Basic Bayesian concepts and methods with emphasis on data analysis. Special emphasis on specification of prior distributions. Development for one-two samples and on to binary, Poisson, and linear regression. Analyses performed using free OpenBugs software. Mine Dogucu

STATS 120 STATS 120ALecture, three hours; discussion, one to two hours. Introductory course covering basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation. Only one course from Statistics 120A, Mathematics 130A, and Mathematics 132A may be taken for credit. Weining Shen (2)

STATS 120 STATS 120BLecture, three hours; discussion, one to two hours. Introductory course covering basic principles of probability and statistical inference. Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference. Tianchen Qian (2)

STATS 120 STATS 120CLecture, three hours; discussion, one to two hours. Introductory course covering basic principles of probability and statistical inference. Linear regression, analysis of variance, model checking. Hengrui Cai (2)

STATS 170 STATS 170AProblem definition and analysis, data representation, algorithm selection, solution validation, and results presentation. Students do team projects and lectures cover analysis alternatives, project planning, and data analysis issues. First quarter emphasizes approach selection, project planning, and experimental design. Babak Shahbaba

STATS 170 STATS 170BProblem definition and analysis, data representation, algorithm selection, solution validation, and results presentation. Students do team projects and lectures cover analysis alternatives, project planning, and data analysis issues. Second quarter emphasizes project execution and analysis, and presentation of results. Babak Shahbaba