Whether you want to try something for the first time, or dive deep into your area of study, our courses offer you the opportunity to shine a light on what interests you. 

Please note: The Course Catalog should be used for all official planning. 

STAT - Statistics

STAT 107: Principles of Statistics

For students in all disciplines. Provides the background needed to evaluate statistical arguments found in newspapers, magazines, reports, and journals and the logic and techniques necessary to perform responsible elementary statistical analysis. Topics include basic data analysis, one-variable regression, experimental and sampling design, random variables, sampling distributions, and inference (confidence intervals and significance testing). This course may not be taken on a Satisfactory/Unsatisfactory basis. Students with credit for MATH 140 or equivalent, or BIOL 170, or AP Statistics should not take this course and should instead consider STAT 255.
Units: 6

STAT 205: Data-Scientific Programming

An introduction to programming with emphasis on learning from data in order to gain useful insights. Topics focus on elementary programming concepts in the R language and the necessary tools to handle, analyze and interpret data. This course will be taught in a workshop format, and students will complete regular assignments and a final project that provide hands-on programming/analysis experiences.
Units: 6
Also listed as Computer Science 205
Prerequisite: One prior course MATH, STAT, or CMSC course, or BIOL 170, or consent of instructor

STAT 208: Machine Learning

An overview of techniques used to discover structural patterns and make predictions using complex datasets that are prevalent in today's world. The central machine learning tasks of classification, clustering, and regression will be explored, along with methods for training models and evaluating predictions. This course will be taught in a workshop format. Assignments will involve the use of statistical software.
Units: 6
Also listed as Linguistics 208, Computer Science 208
Prerequisite: CMSC 150, or CMSC 205, or CMSC 210, or consent of instructor

STAT 255: Statistics for Data Science

This course introduces modern statistical techniques in the context of predictive inference and modeling. Topics will include data analysis techniques such as linear and logistic regression, ANOVA, nonparametric methods, and computational approaches such as cross-validation and bootstrapping. Statistical software will be used frequently. This class will involve regular in-class and out-of-class assignments as well as exams and quizzes.
Units: 6
Prerequisite: STAT 107, BIOL 170, or MATH 140, or instructor permission

STAT 340: Probability

An introduction to probability and its applications. Topics will include combinatorial and axiomatic probability, conditional probability and Bayes' Theorem, random variables, expectation and variance, discrete and continuous probability distributions, joint and conditional distributions, and limit laws.
Units: 6
Also listed as Mathematics 340
Prerequisite: MATH 200, and either MATH 220 or MATH 230

STAT 390: Tutorial Studies in Statistics

Advanced work in statistics on topics not covered in regular offerings.
Units: 1 TO 98
Prerequisite: Counter Registration Required.

STAT 391: Directed Study in Statistics

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work.
Units: 1 TO 98
Prerequisite: Counter Registration Required.

STAT 399: Independent Study in Statistics

Guided independent study of an advanced topic in undergraduate statistics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper.
Units: 1 TO 98
Prerequisite: Counter Registration Required.

STAT 405: Advanced Data Computing

This course builds on CMSC/STAT 205, providing a deeper exploration of statistical computing in R. Topics might include efficient programming techniques, parallelization, statistical algorithms, advanced data visualization, and creation of R packages. Statistical software will be used extensively in this course. The class will be taught in an interactive lab-based format. There will be regular assignments and a project.
Units: 6
Also listed as Computer Science 405
Prerequisite: CMSC 205

STAT 445: Mathematical Statistics

Development of the mathematical theory of statistics and its application to the real world. The course will focus on the principles of estimation and testing from both the frequentist and Bayesian perspectives. Resampling methods (permutation tests and bootstrap intervals) will also be explored.
Units: 6
Prerequisite: MATH/STAT 340

STAT 450: Bayesian Statistics

A study of the Bayesian statistical philosophy, contrasting it with the traditional frequentist approach taught in other statistics courses. Topics include Bayes' Theorem, prior and posterior probability distributions, hierarchical models, and Markov Chain Monte Carlo methods. The course will involve a mixture of lecture, discussion, and use of statistical software. Requirements include exams, a project, and assignments involving the use of statistical software.
Units: 6
Prerequisite: MATH/STAT 340

STAT 455: Advanced Statistical Modeling

This course expands on STAT 255, and introduces more sophisticated models, meant to capture complicated correlation structure in data. Topics might include generalized linear models, mixed-effects models, hierarchical models, spatial models, and time series. The course will involve the use of statistical software. There will be regular assignments, exams, and possibly projects.
Units: 6
Prerequisite: STAT 255 or instructor permission

STAT 590: Tutorial Studies in Statistics

Units: 1 TO 98
Prerequisite: Counter Registration Required.

STAT 591: Directed Study in Statistics

Directed study follows a syllabus set primarily by the instructor to meet the needs or interests of an individual student or small group of students. The main goal of directed study is knowledge or skill acquisition, not research or creative work.
Units: 1 TO 98
Prerequisite: Counter Registration Required.

STAT 699: Independent Study in Statistics

Guided independent study of an advanced topic in undergraduate statistics or supervised work on an undergraduate research project, generally culminating in a final presentation and/or paper.
Units: 1 TO 98
Prerequisite: Counter Registration Required.