Statistics and Data Science Lab
The Statistics and Data Science Lab (SDSL) is a research facility which offers services pertaining to statistical methodology, experimental design, data analytics, and data visualization for faculty members at Florida Gulf Coast University. SDSL also serves the Southwest Florida community, and beyond, by providing assistance in areas crucial to the scientific process and knowledge discovery that are heavily reliant on data.
SDSL is housed under the Department of Mathematics within the College of Arts and Sciences. It provides expert consulting services to students, faculty, researchers, and external organizations. In today’s data-driven world. SDSL aims to bridge the gap between data collection and effective analysis, helping stakeholders to make informed decisions using sound statistical principles.
Services
Experimental Design
Provide insight into experimental design to help experimenters choose appropriate designs prior to their experiments and assist in the delivery of experimental results using applicable statistical methods.
Statistical Data Analysis
Analysis of data gathered from experiments, observational studies, and other data sources. Analyses include visualization, management, inference, and revising conclusions based on newer data.
Big Data Analysis
Analysis of data that require significant computational power and have a higher degree of complexity in data handling. Assist with management of high dimensional data and proper use of algorithms specific to such data.
Interdisciplinary Research
Support researchers in statistical analyses across disciplines in STEAM to address important issues and to deliver inferences using methods developed by the statistical community.
Scholarly Work
Support researchers (faculty, students, and broader scientific community) with dissertations, grants, and publications (books, journal articles etc.)
Engagement
Enhance knowledge of researchers in statistical tools that are efficient, new, and precise. Train researchers to handle tools with recent statistical platforms such as R, Python, and SQL.
Operational Infrastructure
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Framework
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Funding
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Clients
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Quality Control
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Outreach
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Additional Information
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Faculty and Staff
Have Questions?
SDSL is committed to increasing scientific output by validating results with evidence based analysis grounded in statistical principles and data analytic foundations. Please feel free to contact us.