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. We can assist with study design and statistical planning for grant proposals, help with data visualization and presentation, consult on the choice and application of statistical methods, aid in understanding and interpreting statistical analysis, and more.
Consultations are free to the University of Virginia research community. To set up an appointment (typically 1 hour), email us at email@example.com. To help us make the best use of our time, please describe your overall research goals and any specific questions you have. Keep in mind that it can take several meetings to completely address many questions. We want to provide the best possible help and this often requires some time to ponder on our own.
Staff expertise 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.
- Email firstname.lastname@example.org for help. We are available to work with you via email or Zoom. In-person consultations are suspended indefinitely as of March 16, 2020.
- View our growing collection of helpful articles on data analysis and statistical practice.
- Have a look at our current and past workshop materials.
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.