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OverviewMake smarter decisions by mastering causal reasoning and causal inference. Learn how to separate correlation from causation, evaluate impact, and apply evidence-based thinking—no complex math required. Key Features Learn how to separate causation from correlation in real decisions Apply causal inference methods without complex statistics Practice causal thinking with real cases and an interactive app Book DescriptionIn a world dominated by data and correlations, making good decisions requires understanding what truly causes what. The Causal Mindset Handbook is a clear, non-technical guide to causal reasoning and causal inference, designed to help readers think more clearly about cause and effect. Rather than focusing on complex statistics, the book introduces intuitive concepts and visual tools, such as causal graphs and counterfactual thinking, to evaluate claims, measure impact, and avoid common reasoning traps. Readers learn how causal inference differs from predictive models, and why correlation alone is not enough for sound decision-making. Drawing on real-world case studies from business, policy, and everyday life, the book shows how causal thinking works when perfect experiments are not possible. Designed for managers, analysts, policymakers, and curious professionals, it combines hands-on exercises with access to an interactive companion app, enabling readers to practice evidence-based decision-making with confidence. Foreword by Pr. Karim R. Lakhani, Harvard Business School, Digital Data Design Institute at Harvard, Laboratory for Innovation Science at Harvard.What you will learn Understand causality and why correlation can mislead decisions Distinguish predictive models from causal inference Use causal graphs to reason about cause and effect Evaluate impact with experiments and quasi-experiments Spot flawed causal claims in business and everyday life Apply causal thinking confidently to real decisions Who this book is forThis book is ideal for decision-makers, managers, analysts, marketers, policymakers, and curious professionals who want to improve how they evaluate evidence and make decisions. No prior background in statistics, economics, or programming is required. It is suited for readers who work with data, experiments, or performance metrics and want to better understand cause and effect without diving into technical or mathematical detail. Full Product DetailsAuthor: Dr. Quentin Gallea , Pr. Karim R. LakhaniPublisher: Packt Publishing Limited Imprint: Packt Publishing Limited ISBN: 9781806117857ISBN 10: 1806117851 Pages: 212 Publication Date: 06 March 2026 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Forthcoming Availability: In Print Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock. Table of ContentsTable of Contents Understanding Causality and Its Importance Causation versus Prediction Why Is It So Hard To Prove Causality? Beyond Correlation: The Main Culprits The Causal Mindset Framework Randomized Experiment Quasi-Experimental Methods Correct Answer, Wrong Question: The Importance of Choosing the Right Metrics Embracing UncertaintyReviewsAuthor InformationWith deep expertise and a passion for causality, Dr. Quentin Gallea has published research in top journals, addressing timely issues like the effects of COVID lockdowns or weapon imports on conflict. He is known for his unique ability to make complex topics accessible without compromising rigor. His practical approach has empowered over 15,000 people from C-suites to experienced researchers to apply causal thinking and causal inference in their respective fields. Today, Quentin is self-employed and provides advisory, training, public speaking, and advisory services across the world with a particular focus on measuring the impact of AI. In addition, he is a Senior Advisor at Enlighten Advisory, offering his expertise to support strategic decisions. Tab Content 6Author Website:Countries AvailableAll regions |
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