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

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

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

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

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

Scholarly Work

Support researchers (faculty, students, and broader scientific community) with dissertations, grants, and publications (books, journal articles etc.)

Engagement

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

  • 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

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Bianco, Nicholas
Instructor II
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Assistant Professor, Mathematics
Statistics and Applied Mathematics
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Program Coordinator/Professor, Mathematics

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. 

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Associate Dean, Honors College
SH 0204