Statistical Analysis
Hypothesis testing, regression, survey analysis, and descriptive statistics
Data Visualization
Tableau, Power BI, and Python dashboards that communicate clearly
Predictive Modeling
Forecasting, classification, and clustering with scikit-learn and R
Geospatial Analysis
Mapping, spatial clustering, and GIS-based community insights
The Process
From Intake to Deliverable
Every Impacts Lab project follows a structured engagement model — rigorous enough for real results, flexible enough for diverse challenges.
1) Intake & Scoping
Client submits a project brief. Faculty and lab leads assess scope, feasibility, and data availability.
2) Team Assignment
3–5 student analysts matched to the project based on skills and interests. Faculty supervisor assigned.
3) Discovery Sprint
Kickoff meeting with client. Data ingested, cleaned, and explored. Problem defined precisely.
4) Analysis & Modeling
Core analytical work: statistical analysis, visualization, modeling, and insight generation.
5) Deliverable & Presentation
Final report, dashboard, or dataset delivered. Public presentation at semester's end.
Eligible Partner Organizations
The Impacts Lab gives priority to organizations serving communities in the Greater New Orleans area.
Government Agencies
City, parish, and state agencies with public data and policy needs.
Nonprofits
501(c)(3) organizations serving health, education, housing, or environment.
Schools & Universities
K–12 schools, charter networks, and higher education institutions.
Social Enterprises
Mission-driven businesses with a clear community or environmental focus.