30 courses with the subject STAT, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
STAT 1100Chance: An Introduction to Statistics3
Effective Date 08/01/2022 This course studies introductory statistics and probability, visual methods for summarizing quantitative information, basic experimental design and sampling methods, ethics and experimentation, causation, and interpretation of statistical analyzes. Applications use data drawn from various current sources, including journals and news. No prior knowledge of statistics is required. Students will not receive credit for both STAT 1100 and STAT 1120.
Effective Date 08/01/2022 This course includes graphical displays of data, relationships in data, design of experiments, causation, random sampling, probability distributions, inference, confidence intervals, tests of hypotheses, and regression and correlation. No prior knowledge of statistics is required. Students will not receive credit for both STAT 1100 and STAT 1120.
Effective Date 01/01/2021 These statistics classes are for students in the UVA Edge program. They help students develop critical data analysis skills for academia, the workplace and life. See https://edge.virginia.edu/ for details.
Effective Date 08/01/2026 This course provides an introduction to the process of collecting, manipulating, exploring, analyzing, and displaying data using the statistical software R. The collection of elementary statistical analysis techniques introduced will be driven by questions derived from the data. The data used in this course will generally follow a common theme. No prior knowledge of statistics, data science, or programming is required.
STAT 1602Introduction to Data Science with Python3
Effective Date 08/01/2022 This course provides an introduction to various topics in data science using the Python programming language. The course will start with the basics of Python, and apply them to data cleaning, merging, transformation, and analytic methods drawn from data science analysis and statistics, with an emphasis on applications. No prior knowledge of statistics, data science, or programming is required.
Effective Date 08/01/2022 This course includes a basic treatment of probability, and covers inference for one and two populations, including both hypothesis testing and confidence intervals. Analysis of variance and linear regression are also covered. Applications are drawn from biology and medicine. No prior knowledge of statistics is required.
Concurrent enrollment in a lab section of STAT 2020. Credits: 4
STAT 2120Introduction to Statistical Analysis4
Effective Date 08/01/2022 This course provides an introduction to the probability & statistical theory underlying the estimation of parameters & testing of statistical hypotheses, including those in the context of simple & multiple regression Applications are drawn from economics, business, & other fields. No prior knowledge of statistics is required. Highly Recommended: Prior experience with calculus I;
Effective Date 08/01/2026 This course introduces advanced statistical methods used in biostatistics and public health research. Topics include study designs, survival analysis, longitudinal and repeated-measures data analysis, odds ratios and logistic regression, and core concepts in epidemiology. Emphasis on applying statistical methods to real-world health and biological data with R, evaluating public health studies, interpreting results, and communicating findings clearly.
A prior course in statistics. Requisites Completed one of STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110, or APMA 3120. Students cannot enroll if they have previously completed STAT 3559 Topic #13 Credits: 3
STAT 3080From Data to Knowledge3
Effective Date 08/01/2024 This course introduces methods to approach uncertainty and variation inherent in elementary statistical techniques from multiple angles. Simulation techniques such as the bootstrap will also be used. Conceptual discussion in lectures is supplemented with hands-on practice in applied data-analysis tasks using R.
A prior course in statistics and a prior course in programming. Requisites Students must have completed ONE of STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110, APMA 3120 & ONE of STAT 1601, STAT 1602, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 3110Foundations of Statistics3
Effective Date 08/01/2025 This course provides an overview of basic probability and matrix algebra required for statistics. Topics include sample spaces and events, properties of probability, conditional probability, discrete and continuous random variables, expected values, joint distributions, matrix arithmetic, matrix inverses, systems of linear equations, eigenspaces, and covariance and correlation matrices.
A prior course in calculus II. Requisites Must have completed Math 1220 or MATH 1320 or APMA 1110 or MATH 2310 or MATH 2315 or APMA 2120. Credits: 3
STAT 3120Introduction to Mathematical Statistics3
Effective Date 08/01/2022 This course provides a calculus-based introduction to mathematical statistics with some applications. Topics include: sampling theory, point estimation, interval estimation, testing hypotheses, linear regression, correlation, analysis of variance, and categorical data.
A prior course in probability. Requisites Must have completed MATH 3100 or APMA 3100 or STAT 3110 Credits: 3
STAT 3130Design and Analysis of Sample Surveys3
Effective Date 08/01/2024 This course introduces main designs & estimation techniques used in sample surveys; including simple random sampling, stratification, cluster sampling, double sampling, post-stratification, ratio estimation; non-response problems, measurement errors. Properties of sample surveys are developed through simulation procedures.
A prior course in statistics. Requisites Students must have completed ONE of the following: STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110 or APMA 3120 Credits: 3
STAT 3220Introduction to Regression Analysis3
Effective Date 08/01/2024 This course provides a survey of regression analysis techniques, covering topics from simple regression, multiple regression, logistic regression, and analysis of variance. The primary focus is on model development and applications.
A prior course in statistics. Requisites Students must have completed ONE of the following: STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110 or APMA 3120 Credits: 3
STAT 3250Data Analysis with Python3
Effective Date 08/01/2024 This course provides an introduction to data analysis using the Python programming language. Topics include using an integrated development environment; data analysis packages numpy, pandas and scipy; data loading, storage, cleaning, merging, transformation, and aggregation; data plotting and visualization.
A prior course in statistics and a prior course in programming. Requisites Students must have completed ONE of the following: STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110 or APMA 3120 Credits: 3
STAT 3280Data Visualization and Management3
Effective Date 08/01/2024 This course introduces methods for presenting data graphically and in tabular form, including the use of software to create visualizations. Also introduced are databases, with topics including traditional relational databases and SQL (Structured Query Language) for retrieving information.
A prior course in statistics and a prior course in R programming. Requisites Students must have completed ONE of STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110, or APMA 3120 & ONE of STAT 1601 or STAT 3080 Credits: 3
STAT 3480Nonparametric and Rank-Based Statistics3
Effective Date 08/01/2024 This course includes an overview of parametric vs. non-parametric methods including one-sample, two-sample, and k-sample methods; pair comparison and block designs; tests for trends and association; multivariate tests; analysis of censored data; bootstrap methods; multi-factor experiments; and smoothing methods.
A prior course in statistics. Requisites Students must have completed ONE of the following STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110 or APMA 3120 Credits: 3
STAT 3559New Course in Statistics1
Effective Date 05/01/2026 This course provides the opportunity to offer a new topic in the subject area of Statistics.
Effective Date 08/01/2024 This course includes linear regression models, inferences in regression analysis, model validation, selection of independent variables, multicollinearity, influential observations, and other topics. Conceptual discussion is supplemented with hands-on practice in applied data-analysis tasks. Highly recommended: A prior course in applied regression such as STAT 3220.
A prior course in statistics and a prior course in linear algebra. Requisites Students must have completed ONE of the following STAT 1100, STAT 1120, STAT 2020, STAT 2120, STAT 3120, APMA 3110 or APMA 3120 & ONE of STAT 3110, MATH 3350, MATH 3351, APMA 3080 Credits: 3
STAT 4130Applied Multivariate Statistics3
Effective Date 08/01/2022 This course develops fundamental methodology to the analysis of multivariate data using computational tools. Topics include multivariate normal distribution, multivariate linear model, principal components and factor analysis, discriminant analysis, clustering, and classification.
A prior course in mathematical statistics, a prior course in linear algebra, and a prior course in programming. Requisites Students must have completed STAT 3120 & ONE of STAT 3110, MATH 3350, MATH 3351, APMA 3080 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 4160Experimental Design3
Effective Date 08/01/2022 This course introduces various topics in experimental design, including simple comparative experiments, single factor analysis of variance, randomized blocks, Latin squares, factorial designs, blocking and confounding, and two-level factorial designs. The statistical software R is used throughout this course.
A prior course in regression. Requisites Students must have completed ONE of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 Credits: 3
STAT 4170Financial Time Series and Forecasting3
Effective Date 08/01/2022 This course introduces topics in time series analysis as they relate to financial data. Topics include properties of financial data, moving average and ARMA models, exponential smoothing, ARCH and GARCH models, volatility models, case studies in linear time series, high frequency financial data, and value at risk.
A prior course in probability, a prior course in regression, and a prior course in programming. Requisites Students must have completed ONE of STAT 3110, MATH 3100, APMA 3100 & ONE of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 4220Applied Analytics for Business3
Effective Date 08/01/2022 This course focuses on applying data analytic techniques to business, including customer analytics, business analytics, and web analytics through mining of social media and other online data. Several projects are incorporated into the course.
A prior course in regression and a prior course in programming. Requisites Students must have completed ONE of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 4440Bayesian Statistical Analysis3
Effective Date 08/01/2026 This course provides an introduction to statistical modeling, data analysis, and computation from a Bayesian perspective. Topics include conditional probability, prior and posterior distributions, elementary Bayesian models, simulation approaches to Bayesian computation, hierarchical models, Bayesian regression, and predictive model checking.
A prior course in probability, a prior course in regression, and a prior course in programming. Requisites Completed one of STAT 3110, MATH 3100, or APMA 3100; AND one of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, or SYS 4021; AND one of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, or CS 1113 Credits: 3
STAT 4559New Course in Statistics1
Effective Date 08/01/2026 This course provides the opportunity to offer a new topic in the subject area of Statistics.
Effective Date 08/01/2022 This course introduces various topics in machine learning, including regression, classification, resampling methods, linear model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. The statistical software R is incorporated throughout.
A prior course in regression and a prior course in programming. Requisites Students must have completed ONE of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 4800Advanced Sports Analytics I3
Effective Date 08/01/2022 This course provides a platform for exploring advanced statistical modeling and analysis techniques through the lens of state-of-the-art sports analytics.
A prior course in mathematical statistics, a prior course in regression, and a prior course in programming. Requisites Students must have completed STAT 3120 AND One of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 AND One of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
STAT 4993Independent Study1
Effective Date 01/01/2016 Reading and study programs in areas of interest to individual students. For students interested in topics not covered in regular courses. Students must obtain a faculty advisor to approve and direct the program.
Effective Date 08/01/2022 Students will work in teams on a capstone project. The project will involve significant data preparation and analysis of data, preparation of a comprehensive project report, and presentation of results. Many projects will come from external clients who have data analysis challenges.
A prior course in regression and a prior course in programming. This course is restricted to Statistics majors in their final year. Requisites Students must have completed ONE of STAT 3220, STAT 4120, STAT 5120, ECON 3720, ECON 4720, SYS 4021 & ONE of STAT 1601, STAT 1602, STAT 3080, STAT 3250, CS 1110, CS 1111, CS 1112, CS 1113 Credits: 3
Source: University of Virginia-Main Campus's catalog, linked per course · table learning_unit · CourseShelf publish 59
