2 Introduction
3 Introduction
This portfolio represents the evolution of my previous Bookdown project into a fully reproducible Quarto Book. While the original project focused on completing assignments, this version reflects refinement, organization, and intentional presentation. I approached this revision not just as a technical conversion, but as an opportunity to improve clarity, structure, and reproducibility.
Across these chapters, I analyze data from a variety of domains, including:
- Crime and public safety
- Civic complaint data (NYC 311)
- Demographic predictors of income
- Streaming behavior
- Exercise and sleep outcomes
- Sports performance analytics
Each analysis follows a consistent workflow: data cleaning, visualization, statistical testing or modeling, and careful interpretation. My goal was to ensure that every result presented in this book is directly generated from code and clearly explained.
All analyses in this book are fully reproducible. Every table, figure, and statistical result is generated directly from the code shown in each chapter.
3.1 Why This Portfolio Matters
This project reflects my growth in statistical reasoning and data analysis. Over time, I have become more intentional about:
- Writing clear interpretations instead of just reporting output
- Structuring code so that it is readable and reproducible
- Creating publication-quality tables and figures
- Thinking critically about what statistical results actually mean
Converting this project to Quarto allowed me to strengthen those skills while adopting a modern publishing workflow used in professional research environments.
3.2 What Readers Can Expect
Readers will find:
- Cleanly labeled figures and tables
- Transparent modeling decisions
- Clear explanations of statistical results
- Applied conclusions grounded in data
More than anything, this portfolio demonstrates my ability to move beyond running statistical tests and toward communicating meaningful insights in a structured, reproducible way.