Model to Meaning
Model to Meaning
How to Interpret Statistical Models with R and Python
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Sign in or Sign up!- Release Date: 28/09/2025
- Barcode: 9781032908724
- Imprint: CRC Press
- Publisher: Taylor & Francis

Model to Meaning
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DESCRIPTION
How to Interpret Statistical Models with R and Python Proposes a consistent workflow that can be applied to (almost) any statistical or machine learning model. Readers will learn how to transform complex parameter estimates into quantities that are readily interpretable, intuitive, and understandable. Our world is complex. To make sense of it, data analysts routinely fit sophisticated statistical or machine learning models. Interpreting the results produced by such models can be challenging, and researchers often struggle to communicate their findings to colleagues and stakeholders. Model to Meaning is a book designed to bridge that gap. It is a practical guide for anyone who needs to translate model outputs into accurate insights that are accessible to a wide audience. Features: Model to Meaning introduces a simple and powerful conceptual framework to help analysts describe the statistical quantities that can shed light on their research questions, estimate those quantities, and communicate the results clearly and rigorously. Based on this framework, the book proposes a consistent workflow that can be applied to (almost) any statistical or machine learning model. Readers will learn how to transform complex parameter estimates into quantities that are readily interpretable, intuitive, and understandable. Written for data scientists, researchers, and students, the book speaks to newcomers seeking practical skills, and to experienced analysts who are ready to adopt new tools and rethink entrenched habits. It offers useful ideas, concrete workflows, powerful software, and detailed case studies, presented using real-world data and code examples.
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