StatLab, part of the University of Virginia Library, is a consulting group that supports researchers in the areas of statistics and data science. Members of the UVA community can contact us at [email protected] to set up a free consultation.
We help with a range of challenges, including:
- Data wrangling and cleaning
- Sample size and power estimation
- Selecting, implementing, and intepreting statistical methods
- Model evaluation
- Data visualization
- Debugging statistical software
We also offer free workshops and write articles about statistics and data science.
In collaboration with graduate student fellows, we produce statistical-programming resources and host them here on GitHub:
- Statistical Modeling Examples in R: Worked examples of statistical modeling in R, including linear regression, logistic regression, count modeling, and multilevel modeling. Published using R Markdown and occasionally updated.
- Python and R: A book providing parallel code examples in Python and R to help analysts and researchers translate between and learn the languages. Published in 2021 using bookdown and no longer updated. (Mostly obsolete thanks to AI)
We also use GitHub to host resources to help us with consultations and StatLab articles:
- Consulting resources: A list of selected bookmarks to sites we frequently reference
- R to Stata Cheatsheet: Common statistical tasks in R translated to Stata. (Mostly obsolete thanks to AI)
- Accessibility Checklist: Reference to help us develop more accessible materials
- GitHub Guide: StatLab guide to Git branching, merging, and stashing
- R install and update: Installing and Updating R, RStudio and R Packages
- SQLite Notes: A quick reference to SQL via SQLite
If you find a resource on our GitHub or a StatLab article useful to your work, please consider an acknowledgment. A citation example for StatLab articles is here. And when a license is included in a repository on our GitHub, please follow its terms.