Jordan Rodu headshot
JR

Jordan Scott Rodu

Assistant Professor
Unit: College of Arts and Sciences
Department: Department of Statistics
Office location and address
Halsey Hall 104
148 Amphitheater Way
Charlottesville, Virginia 22904
Education
Ph.D University of Pennsylvania - The Wharton School
The Conductor's Institue of Bard College
B.A., Williams College
STAT 1800: Introduction to Sports Analytics
Credits: 3
This course provides an introduction to sports analytics, including the collection, analysis, and visualization of sports data using the statistical programming language R. Elementary statistical analysis techniques will be introduced through questions arising in sports.
STAT 4310: Data Visualization and Presentation
Credits: 3
Introduces methods for effectively presenting data both visually and in table form. Software used will include the open-source R and Tableau visualization software. Students will work together on team projects developing reports and presentations to be presented to the class.
STAT 4559: New Course in Statistics
Credits: 1–4
This course provides the opportunity to offer a new topic in the subject area of Statistics.
STAT 4630: Statistical Machine Learning
Credits: 3
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. Prerequisite: STAT 3220, STAT 5120, or ECON 3720, and previous experience with R.
STAT 4800: Advanced Sports Analytics I
Credits: 3
This course provides a platform for exploring advanced statistical modeling and analysis techniques through the lens of state-of-the-art sports analytics.
STAT 4993: Independent Study
Credits: 1–4
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.
STAT 4996: Capstone
Credits: 3
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.
STAT 5630: Statistical Machine Learning
Credits: 3
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. Prerequisite: STAT 5120, STAT 6120, or ECON 3720, and previous experience with R Prerequisite: STAT 5120, STAT 6120, or ECON 3720, and previous experience with R
STAT 9999: Non-Topical Research
Credits: 1–12
For doctoral research, taken under the supervision of a dissertation director.