{"product_id":"9780262037310","title":"Elements of Causal Inference","description":"\u003cp\u003e\u003cstrong\u003eElements of Causal Inference\u003c\/strong\u003e explores the fundamental principles and methodologies of causal inference, a critical aspect in the fields of statistics and machine learning. Written by esteemed authors Jonas Peters, Dominik Janzing, and Bernhard Schölkopf, this book serves as a comprehensive guide for both researchers and practitioners seeking to understand the intricacies of causal relationships.\u003c\/p\u003e\n\n\u003ch3\u003eThe Story\u003c\/h3\u003e\n\u003cp\u003eDelving into the complex world of causality, the authors present a structured framework that bridges the gap between theoretical constructs and practical applications. Through a series of insightful chapters, they dissect various causal models and the assumptions that underpin them, making complex concepts accessible to readers from diverse backgrounds. The narrative is enriched with illustrative examples that demonstrate how causal inference can be applied to real-world problems.\u003c\/p\u003e\n\n\u003ch3\u003eWhy Readers Love It\u003c\/h3\u003e\n\u003cul\u003e\n    \u003cli\u003e\n\u003cstrong\u003eClarity of Explanation:\u003c\/strong\u003e The authors excel in elucidating intricate statistical principles, making them digestible for both novice and experienced readers.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003ePractical Applications:\u003c\/strong\u003e The book is replete with case studies that highlight the relevance of causal inference in contemporary research and data analysis.\u003c\/li\u003e\n    \u003cli\u003e\n\u003cstrong\u003eInterdisciplinary Approach:\u003c\/strong\u003e Addressing a breadth of topics, the book appeals to statisticians, data scientists, and social scientists alike.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003ePerfect For\u003c\/h3\u003e\n\u003cp\u003eThis book is ideal for students, researchers, and professionals interested in advancing their understanding of causal inference. It also complements works like \u003cstrong\u003eElements of Statistical Learning\u003c\/strong\u003e by Hastie, Tibshirani, and Friedman, providing a holistic view of statistical modelling techniques.\u003c\/p\u003e \n\n\u003cblockquote\u003e\n\u003cp\u003e“An essential read for anyone looking to deepen their understanding of the causal structure underlying their data.”\u003c\/p\u003e\n\u003c\/blockquote\u003e","brand":"MIT Press Ltd","offers":[{"title":"Default Title","offer_id":56228997693772,"sku":"9780262037310","price":43.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0960\/4163\/2076\/files\/9780262037310_f0c7f5da-d38b-4f9c-89f8-2953094a701d.webp?v=1765663494","url":"https:\/\/foxandfablebooksellers.com\/fr\/products\/9780262037310","provider":"Fox \u0026 Fable UK","version":"1.0","type":"link"}