Models for Non-Modelers: Understanding the Use of Models for Social Scientists and Others

Models for Non-Modelers is a book that teaches non-modelers to understand and critically appraise data and statistical models. It includes worked examples and boxed text for more technical aspects and examines AI and causality. It is suitable for graduate students and researchers in the social sciences.

Format: Hardback
Length: 144 pages
Publication date: 18 August 2023
Publisher: Taylor & Francis Ltd

Models for Non-Modelers is a comprehensive guide that aims to empower non-modelers, particularly social scientists, with the knowledge and skills necessary to understand and critically evaluate models. While data and statistical models are widely employed in disciplines such as epidemiology, climate science, and systems design, their complexity can pose significant challenges for individuals without the requisite training. This book is specifically designed to address this gap and provide a valuable resource for non-modelers.

The book begins by delving into the fundamentals of modeling, including its purpose, types, and assumptions. It then proceeds to explore a range of common models, both in visual and text form, to facilitate a deeper understanding of their underlying principles and applications. Through extensive examination of these models, the book demonstrates how non-modelers can grasp the complexities of these models, both in terms of their logical structure and practical implementation.

In-depth worked examples and boxed text are included to provide additional clarity and technical details, making the content accessible to readers with varying levels of mathematical expertise. The book also addresses the issue of causality, particularly in the context of AI, and examines how models can contribute to our understanding of complex phenomena.

This book is an invaluable resource for graduate students and researchers in the social sciences who seek to enhance their understanding of models and their application in their research. It provides a step-by-step approach to assessing models, covering topics such as identifying assumptions, evaluating validity, and interpreting results. Additionally, it serves as a primer for those taking first courses in quantitative methods and statistical analysis for research data analysis.

By empowering non-modelers with the skills to evaluate and apply models effectively, Models for Non-Modelers contributes to the advancement of scientific inquiry and evidence-based decision-making. It is a must-read for anyone interested in expanding their knowledge and expertise in the field of modeling and its applications.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032357355