Tutorials and training material
This section hosts practical tutorials, examples, and tools developed by Statistical Consulting Services (SCS) to support reproducible data analysis and research workflows. Materials range from short, focused guides (e.g., implementing logistic regression in R) to interactive tools (e.g., Shiny applications for urn randomization).
Most resources are hosted externally on GitHub Pages and are freely available for learning, teaching, and adaptation. All data and code are provided via public GitHub repositories associated with each Page. These materials are intended to complement—rather than replace—consultation or collaboration with SCS.
Statistical Methods in R
Logistic Regression
A step‑by‑step tutorial demonstrating model fitting, interpretation, and common pitfalls using reproducible R code.
View tutorial (GitHub Pages)
Repeated Measures Analysis
A step‑by‑step tutorial on how to examine and analyze data with repeated observations (nested data, longitudinal data, etc.) with reproducible R code.
View tutorial (GitHub Pages)
Study Design & Randomization Tools
Urn Randomization
An R-shiny application for conducting urn randomization with stratification.
View tutorial (GitHub Pages)
Reproducible Research Workflows
msDiaLogue
An R package for the analysis of proteomics and metabolomics data, in collaboration with UConn's PMF Facility
View package overview (GitHub Pages)
Statistical Software
Faculty, staff and students at UConn have access to a wide variety of statistical software. These statistical tools provide varied levels of support for data exploration, analysis and visualization.
Licensed Software
Open Source Software
UConn Anywhere
UConn affiliates can also access software online through UConn Anywhere:
"As an alternative to downloading and installing applications directly onto your computer, you can access the select university-licensed software on your devices through UConn AnyWare."
Access UConn Anywhere via software.uconn.edu/uconn-software-online.