Statistics
51 courses · UC Irvine · 2026-2027 Catalog
Classes: Fall 2026
STATS 5 Seminar in Data Science
- Units
- 1
An introduction to the field of Data Science; intended for entering freshman and transfers.
STATS 6 Introduction to Data Science
- Units
- 4
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.
STATS 7 Basic Statistics
- Units
- 4
Introduces 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.
STATS 8 Introduction to Biological Statistics
- Units
- 4
Introductory statistical techniques used to collect and analyze experimental and observational data from health sciences and biology. Includes exploration of data, probability and sampling distributions, basic statistical inference for means and proportions, linear regression, and analysis of variance.
STATS 67 Introduction to Probability and Statistics for Computer Science
- Units
- 4
- Prerequisite
- MATH 2B or AP Calculus BC with a minimum score of 4
Introduction to the basic concepts of probability and statistics with discussion of applications to computer science.
STATS 68 Statistical Computing and Exploratory Data Analysis
- Units
- 4
- Prerequisite
- (STATS 7 or AP Statistics with a minimum score of 3) and (I&C SCI 31 or I&C SCI H32)
Introduces key concepts in statistical computing. Techniques such as exploratory data analysis, data visualization, simulation, and optimization methods, are presented in the context of data analysis within a statistical computing environment.
STATS 110 Statistical Methods for Data Analysis I
- Units
- 4
- Prerequisite
- STATS 7 or STATS 8 or STATS 67 or AP Statistics with a minimum score of 3 or (STATS 120A and STATS 120B and STATS 120C)
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.
STATS 111 Statistical Methods for Data Analysis II
- Units
- 4
- Prerequisite
- STATS 110
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.
STATS 112 Statistical Methods for Data Analysis III
- Units
- 4
- Prerequisite
- STATS 111
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.
STATS 115 Introduction to Bayesian Data Analysis
- Units
- 4
- Prerequisite
- STATS 120C. Recommended: STATS 110
Basic Bayesian concepts and methods with emphasis on data analysis. Prior and posterior probability distributions, modeling, and Markov Chain Monte Carlo techniques are presented in the context of data analysis within a statistical computing environment.
STATS 120A Introduction to Probability and Statistics I
- Units
- 4
- Prerequisite
- (MATH 2A or AP Calculus AB with a minimum score of 4 or AP Calculus AB Subscore with a minimum score of 4 or AP Calculus BC with a minimum score of 3) and (MATH 2B or AP Calculus BC with a minimum score of 4) and (MATH 2D or MATH 4)
Introduction to basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.
STATS 120B Introduction to Probability and Statistics II
- Units
- 4
- Prerequisite
- STATS 120A
Introduction to basic principles of probability and statistical inference. Point and interval estimation, frequentist hypothesis testing, Bayesian inference, limit theorems, simulation, and the bootstrap.
STATS 120C Introduction to Probability and Statistics III
- Units
- 4
- Prerequisite
- STATS 120B and (MATH 3A or I&C SCI 6N)
Introduction to basic principles of probability and statistical inference. Power and sample size calculation, Neyman-Pearson lemma, (generalized) likelihood ratio test, one-way ANOVA, two-way ANOVA, simple linear regression and its statistical inference and diagnosis, and multiple linear regression.
STATS 140 Multivariate Statistical Methods
- Units
- 4
- Prerequisite
- STATS 120C and (MATH 3A or I&C SCI 6N)
Theory and application of multivariate statistical methods. Topics include statistical inference for the multivariate normal model and its extensions to multiple samples and regression, use of statistical packages for data visualization and reduction, discriminant analysis, cluster analysis, and factor analysis.
STATS 170A Project in Data Science I
- Units
- 4
- Prerequisite
- STATS 68 and SWE 43 and COMPSCI 122A and COMPSCI 178 and I&C SCI 46 and STATS 111
- Corequisite
- STATS 111
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.
STATS 170B Project in Data Science II
- Units
- 4
- Prerequisite
- STATS 170A and STATS 112. In Progress (IP) grade for STATS 170A is also accepted
- Corequisite
- STATS 112
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.
STATS H198 Honors Research
- Units
- 4
Directed independent research in Statistics for ICS honors and Campuswide Honors Collegium students.
STATS 199 Individual Study
- Units
- 2-5
Individual research or investigations under the direction of an individual faculty member.
STATS 200A Intermediate Probability and Statistical Theory
- Units
- 4
- Prerequisite
- STATS 120C with a minimum grade of B-
Basics of probability theory, random variables and basic transformations, univariate distributions—discrete and continuous, multivariate distributions.
STATS 200B Intermediate Probability and Statistical Theory
- Units
- 4
- Prerequisite
- STATS 200A with a minimum grade of B-
Random samples, transformations, limit laws, normal distribution theory, introduction to stochastic processes, data reduction, point estimation (maximum likelihood).
STATS 200C Intermediate Probability and Statistical Theory
- Units
- 4
- Prerequisite
- STATS 200B with a minimum grade of B-
Interval estimation, hypothesis testing, decision theory and Bayesian inference, basic linear model theory.
STATS 201 Statistical Methods for Data Analysis I
- Units
- 4
- Prerequisite
- STATS 7 or STATS 8
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.
STATS 202 Statistical Methods for Data Analysis II
- Units
- 4
- Prerequisite
- STATS 201 with a minimum grade of B- or STATS 210 with a minimum grade of B-
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.
STATS 203 Statistical Methods for Data Analysis III
- Units
- 4
- Prerequisite
- STATS 202 with a minimum grade of B-
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.
STATS 205 Introduction to Bayesian Data Analysis
- Units
- 4
- Prerequisite
- STATS 120C. Recommended: STATS 201 or STATS 210
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.
STATS 205P Bayesian Data Analysis
- Units
- 4
- Prerequisite
- DATA 200AP with a minimum grade of B and DATA 200BP with a minimum grade of B and DATA 210P with a minimum grade of B
Covers basic Bayesian concepts and methods with emphasis on data analysis. Special emphasis on specification of prior distributions. Development of methods and theory for one and two samples, binary, Poisson, and linear regression.
STATS 210 Statistical Methods I: Linear Models
- Units
- 4
- Prerequisite
- Knowledge of basic statistics, calculus, linear algebra
Statistical methods for analyzing data from surveys and experiments. Topics include randomization and model-based inference, two-sample methods, analysis of variance, linear regression and model diagnostics.
STATS 210A Statistical Methods I: Linear Models
- Units
- 4
- Prerequisite
- Knowledge of basic statistics (at the level of STATS 7), calculus, and linear algebra
Statistical methods for analyzing data from surveys and experiments. Topics include randomization and model-based inference, two-sample methods, analysis of variance, linear regression, and model diagnostics.
STATS 210B Statistical Methods II: Categorical Data
- Units
- 4
- Prerequisite
- STATS 210 with a minimum grade of B-. May not be taken for graduate credit by Ph.D. students in Statistics
Introduction to statistical methods for analyzing discrete and non-normal outcomes. Emphasizes the development and application of methods for categorical data, including contingency tables, logistic and Poisson regression, loglinear models.
STATS 210C Statistical Methods III: Longitudinal Data
- Units
- 4
- Prerequisite
- STATS 210B with a minimum grade of B-. May not be taken for graduate credit by Ph.D. students in Statistics
Introduction to statistical methods for analyzing longitudinal outcomes. Emphasizes the development and application of regression methods for correlated and censored outcomes. Methods for continuous and discrete correlated outcomes, as well as censored outcomes, are covered.
STATS 211 Statistical Methods II: Generalized Linear Models
- Units
- 4
- Prerequisite
- STATS 210 (may be taken concurrently) with a minimum grade of B-
Development of the theory and application of generalized linear models. Topics include likelihood estimation and asymptotic distributional theory for exponential families, quasi-likelihood and mixed model development. Emphasizes methodological development and application to real scientific problems.
STATS 212 Statistical Methods III: Methods for Correlated Data
- Units
- 4
- Prerequisite
- STATS 211 with a minimum grade of B-
Development and application of statistical methods for analyzing corrected data. Topics covered include repeated measures ANOVA, linear mixed models, non-linear mixed effects models, and generalized estimating equations. Emphasizes both theoretical development and application of the presented methodology.
STATS 220A Advanced Probability and Statistics Topics
- Units
- 4
- Prerequisite
- STATS 200C with a minimum grade of B-
Advanced topics in probability and statistical inference including measure theoretic probability, large sample theory, decision theory, resampling and Monte Carlo methods, nonparametric methods.
STATS 220B Advanced Probability and Statistics Topics
- Units
- 4
- Prerequisite
- STATS 220A with a minimum grade of B- and MATH 140B
Advanced topics in probability and statistical inference, including measure theoretic probability, large sample theory, decision theory, resampling and Monte Carlo methods, nonparametric methods.
STATS 225 Bayesian Statistical Analysis
- Units
- 4
- Prerequisite
- STATS 205 with a minimum grade of B- and STATS 230 with a minimum grade of B-
Introduction to the Bayesian approach to statistical inference. Topics include univariate and multivariate models, choice of prior distributions, hierarchical models, computation including Markov chain Monte Carlo, model checking, and model selection.
STATS 230 Statistical Computing Methods
- Units
- 4
- Prerequisite
- Two quarters of upper-division or graduate training in probability and statistics
Numerical computations and algorithms with applications in statistics. Topics include optimization methods including the EM algorithm, random number generation and simulation, Markov chain simulation tools, and numerical integration.
STATS 240 Multivariate Statistical Methods
- Units
- 4
- Prerequisite
- STATS 120C and (MATH 3A or I&C SCI 6N)
Theory and application of multivariate statistical methods. Topics include statistical inference for the multivariate normal model and its extensions to multiple samples and regression, use of statistical packages for data visualization and reduction, discriminant analysis, cluster analysis, and factor analysis.
STATS 240P Multivariate Statistical Methods
- Units
- 4
- Prerequisite
- DATA 200AP with a minimum grade of B- and DATA 200BP with a minimum grade of B-
Theory and application of multivariate statistical methods. Topics include statistical inference for the multivariate normal model and its extensions to multiple samples and regression, use of statistical packages for data visualization and dimension reduction, discriminant analysis, cluster analysis, factor analysis.
STATS 245P Time Series Analysis
- Units
- 4
- Prerequisite
- DATA 200AP with a minimum grade of B- and DATA 200BP with a minimum grade of B-
Statistical models for time series. Topics include linear models for trends; stationary time-series; non-stationary time series; forecasting and Kalman filtering; time-series smoothing; seasonal models; ARCH, GARCH and stochastic volatility models; multivariate time series; vector autoregressive models; spectral analysis; case studies.
STATS 262P Theory and Practice of Sample Survey
- Units
- 4
- Prerequisite
- DATA 200AP with a minimum grade of B and DATA 200BP with a minimum grade of B
Basic techniques and statistical methods for designing surveys and analyzing collected survey data. Topics include simple random sampling, ratio and regression estimates, stratified sampling, cluster sampling, sampling with unequal probabilities, multistage sampling, and methods to handle nonresponse.
STATS 265 Causal Inference
- Units
- 4
- Prerequisite
- STATS 200C with a minimum grade of B- and STATS 210 with a minimum grade of B-
Various approaches to causal inference focusing on the Rubin causal model and propensity-score methods. Topics include randomized experiments, observational studies, non-compliance, ignorable and non-ignorable treatment assignment, instrumental variables, and sensitivity analysis. Applications from economics, politics, education, and medicine.
STATS 270 Stochastic Processes
- Units
- 4
- Prerequisite
- STATS 120C
Introduction to the theory and application of stochastic processes. Topics include Markov chains, continuous-time Markov processes, Poisson processes, and Brownian motion. Applications include Markov chain Monte Carlo methods and financial modeling (for example, option pricing).
STATS 270P Stochastic Processes
- Units
- 4
- Prerequisite
- DATA 200AP with a minimum grade of B and DATA 200BP with a minimum grade of B
Introduction to the theory and application of stochastic processes. Topics include Poisson processes, Markov chains, continuous-time Markov processes, and Brownian motion. Applications include Markov chain Monte Carlo methods and financial modeling (e.g. option pricing).
STATS 275 Statistical Consulting
- Units
- 4
- Prerequisite
- STATS 203 with a minimum grade of B or STATS 212 with a minimum grade of B or STATS 210C with a minimum grade of B
Training in collaborative research and practical application of statistics. Emphasis on effective communication as it relates to identifying scientific objectives, formulating a statistical analysis plan, choice of statistical methods, and interpretation of results and their limitations to non-statisticians.
STATS 280 Seminar in Statistics
- Units
- 0.5
Periodic seminar series covering topics of current research in statistics and its application.
STATS 281A Introduction to Probability and Statistics I
- Units
- 4
Introduction to basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.
STATS 281B Introduction to Probability and Statistics II
- Units
- 4
Introduction to basic principles of probability and statistical inference. Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference.
STATS 281C Introduction to Probability and Statistics III
- Units
- 4
Introduction to basic principles of probability and statistical inference. Contingency table analysis, linear regression, analysis of variance, model checking.
STATS 295 Special Topics in Statistics
- Units
- 4
Studies in selected areas of statistics. Topics addressed vary each quarter.
STATS 298 Thesis Supervision
- Units
- 2-12
Individual research or investigation conducted in preparation for the M.S. thesis option or the dissertation requirements for the Ph.D. program.
STATS 299 Individual Study
- Units
- 1-12
Individual research or investigation under the direction of an individual faculty member.