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 Introduces 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 Lecture, 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 Lecture, 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 Lecture, 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 Introduces 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 Lecture, 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 Lecture, 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 Lecture, 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 Basic 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 Lecture, 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 Lecture, 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 Lecture, 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 Problem 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 Problem 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
