Data Science & Discovery Unit
The Data Science & Discovery Unit (DSDU) provides faculty in CEHS resources and services relating to data management and analysis. Specifically, the DSDU offers:
- Collaborating on data planning and data analysis for projects or grants,
- Consulting on data wrangling/handling, database creation, and survey planning,
- Setting up secure databases of archival clinical data, and
- Training on the use of various data tools (e.g., REDCap, Qualtrics, R, MTurk, Jamovi).
Although the DSDU has some overlap with the Statistical Consulting Studio, it is unique in that the focus is on working with data (complex, longitudinal, clinical) including the collection, wrangling, and analysis of the data. The main objective is to aid in working with clinical data; however, other data types are also supported.
The Data Science & Discovery Unit provides consultations regarding data planning, wrangling, and analyzing. This can include:
- Survey creation (REDCap or Qualtrics surveys, planning recruitment)
- Data entry tool set up (for any type of data entry related to research)
- Data planning (formatting, cleaning, reshaping, merging)
- Data analysis (ways that your data can be analyzed, visualized, and reported). Notably, for statistical planning, particularly for graduate students, please contact the Statistical Consulting Studio.
The DSDU provides opportunities for collaboration on projects and grants. These collaborations are generally in the nature where Tyson provides data and statistical expertise as a Co-Investigator or a consultant (depending on the load and need of the project). For significant needs, please contact the DSDU early in the process.
If you have clinical data that you want in a secure, research-accessible database wherein you will be able to access de-identified data for research purposes, please contact the DSDU for more information.
Managing Director: Tyson Barrett
Tyson Barrett is the Managing Director of the Data Science & Discovery Unit. He has a PhD in Quantitative Psychology with a focus on data science and public health. He has worked on grants and published work in a variety of fields within the college. He also teaches graduate level statistics courses (EDUC 6050, EDUC/PSY 6600, EDUC/PSY 7610).