Name: From Basics to Advanced Health Analytics: Exploring Diabetes Data
Start: 2025-12-17T18:00:00+01:00
End: 2025-12-17T20:00:00+01:00

In this session, we will walk through a full end-to-end workflow of health data analysis in R using a simulated database based of diabetes.

We will begin with **exploratory data analysis (EDA)** to identify initial patterns, distributions, and data quality issues. Then, we’ll apply data **wrangling** techniques to prepare the dataset for robust statistical investigation. Building on this foundation, we will create effective and **elegant visualizations** with ggplot2 to communicate insights clearly and intuitively.

Next, we will introduce **inferential modeling** for qualitative outcomes, discussing how to estimate associations, interpret the results, and translate findings into meaningful epidemiological insights.

Finally, we will explore **cluster analysis** to reveal underlying subgroups within the population and highlight the heterogeneity of diabetes profiles.

The session is designed to transition smoothly from basic to more advanced methods, offering a practical and reproducible framework for health data analysis.

No previous experience with medical datasets is required—all code will be shown step by step and shared afterwards.

Federica Gazzelloni

Lucy M

Rafaela Lucas

R-Ladies Rome

R-Ladies

RConsortium

Technology

New Technology

Education & Technology

Software Development

Technology Startups

Women's Networking

Computer Programming

Women's Empowerment

Professional Networking

Women Entrepreneurs

Women in Technology

Web Technology

Women's Business Networking

Open Source

**[Federica Gazzelloni](https://www.linkedin.com/in/federicagazzelloni/)** is an independent researcher, statistician, and instructor specialising in data visualisation, statistical modelling, and data-driven storytelling. She leads R-Ladies Rome and co-organises the Rome R Users Group, promoting inclusive, hands-on learning for the local R and data-science community. Federica collaborates with international organisations, contributes to open-source projects, and develops educational resources spanning R, spatial analysis, and health metrics. She is passionate about building welcoming spaces where people can learn, experiment, and meet others who share a curiosity for data.

**[Rafaela Ribeiro Lucas](https://www.linkedin.com/in/rafaelagrlucas/)** is a Nutritionist with academic training from the Federal University of Pelotas (UFPel) and a postgraduate degree in Eating Behavior from Institute of Research, Teaching, and Health Management (iPGS). And a Master’s degree in Cardiology and Cardiovascular Sciences at the Federal University of Rio Grande do Sul (UFRGS)
Her work is based on methodological and statistical applications in the investigation of cardiovascular risk factors and disease.
She is passionate about Population Epidemiology, Epidemiological Surveillance, and analytical methods for longitudinal studies and complex survey designs.

**[Lucy Michaels](https://www.linkedin.com/in/lucymichaels/)** is a Data Scientist with academic training from Unitelma Sapienza, where she completed a Master’s degree in Analysis and Modeling of Data and Processes. She specialises in applied statistics, machine learning, and analytical modelling for complex real-world problems.
Her recent work focuses on methodological and statistical approaches for understanding pedestrian-accident risk in urban environments, integrating multi-source datasets on visibility, weather, twilight phases, road conditions, and vehicle involvement.
She is passionate about urban mobility analytics, public-health informatics, and data-driven decision-making for safer cities. Her interests include geospatial analysis, mixed-data clustering and designing reproducible analytical pipelines.

R-Ladies Rome

From Basics to Advanced Health Analytics: Exploring Diabetes Data

R-Ladies Rome

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