About this book:

*Data and Devotion: Quantitative Methods for the Study of Religion* provides a comprehensive methodology for applying social science techniques to the study of religious life. The text establishes a framework for translating abstract theological concepts—such as belief, practice, and affiliation—into measurable data while maintaining a rigorous ethical standard of "sacred data stewardship." It emphasizes the importance of thoughtful survey design, sampling strategies, and reproducible workflows, ensuring that quantitative inquiry respects the sensitivities of faith communities while providing a scalable complement to traditional humanistic approaches.

The book details an expansive analytic toolkit, beginning with exploratory data analysis and descriptive statistics before advancing to complex modeling. It introduces researchers to generalized linear models for categorical and count outcomes, as well as multilevel modeling to account for individuals nested within congregations and broader social contexts. The text also bridges the gap between correlation and causation by exploring experimental and quasi-experimental designs, alongside time-series analysis to identify seasonal cycles and long-term trends in religious participation and affiliation.

A significant portion of the work is dedicated to the spatial and computational dimensions of religion. By integrating Geographic Information Systems (GIS), the author demonstrates how to map religious landscapes, analyze accessibility to worship spaces, and employ spatial econometrics to understand regional influences. Furthermore, the book explores cutting-edge computational methods, including natural language processing for analyzing sermons and scriptures, network analysis for mapping community ties, and machine learning for predicting trends like religious disaffiliation.

In its conclusion, the book emphasizes the responsible communication of findings through dashboards, reports, and decision support systems. It argues that the ultimate value of religious data analysis lies in its ability to provide actionable, evidence-based insights for clergy, denominational leaders, and policymakers. By pairing reverence with rigor, the text serves as a practical guide for using modern data science to illuminate the complex, multifaceted dynamics of global devotion without reducing the significance of the spiritual experience.

What You'll Find Inside:

• Comprehensive quantitative methods for studying religion, covering survey design, sampling, statistical inference, and advanced modeling techniques
• Ethical framework for handling 'sacred data' with special attention to privacy, consent, IRB processes, and community partnership principles
• Guidance on operationalizing complex religious concepts like belief, practice, and affiliation into measurable variables with validity and reliability considerations
• Integration of geographic analysis including GIS, spatial statistics, and remote sensing to map religious landscapes and assess accessibility to religious resources
• Modern computational approaches including text analysis, network analysis, machine learning, and digital trace data for studying contemporary religious expression

Who's It For:

This book is designed for social scientists, students, journalists, and data professionals seeking to apply quantitative methods to religious studies. It also serves denominational researchers and staff at religious nonprofits who need evidence-based insights for program evaluation and community understanding. Additionally, civic planners and public officials working to understand the religious dimensions of local life will find practical tools for mapping religious landscapes and assessing accessibility to faith-based resources.