StatLab: Data Analytics
We offer consultations, collaborations, and training in support of data science, applied statistics, and scientific computing, including data wrangling and cleaning, analysis and visualization, statistical inference and computational methods, reproducibility and open science.
Staff expertise also encompasses open source programming languages like R and Python; statistical environments like Stata, SPSS, SAS; scientific computing technologies like Unix, Github, and Overleaf; visualization software (Tableau), and software for qualitative data (Dedoose). We can help with data collection via web scraping and APIs in R and Python and working with structured and unstructured (e.g., text) data. Plus,
- Email us at firstname.lastname@example.org to schedule an appointment,
- View our growing collection of helpful articles on data analysis and statistical practice.
- Have a look at our current and past workshop materials.
- Learn about our Data for Democracy Lab projects.
- We also co-sponsor the UVa UseR Group — come join the fun!
You may also be interested in:
- Our data discovery services, for support finding and understanding existing data sources.
- Our Research Data Management services, for support reviewing data management plans, selecting appropriate active data storage, choosing a repository, and preparing research data for end-of-project archiving.
- Libra Data, UVA’s instance of Dataverse, where you can discover (and deposit) UVA datasets and other scholarly data. To learn more, contact email@example.com.
- Subscribe to our monthly Research Data Services Newsletter to learn about new resources.