Skip to content

Causal Inference in Statistics

Causal Inference in Statistics

MathematicsScience
Pages
156
Published
2016
Language
English

Synopsis

This book addresses the critical role of causality in understanding and utilizing data, a topic often overlooked in introductory statistical texts. It provides a foundational guide to defining causal parameters, understanding necessary assumptions, and expressing these mathematically. Readers will learn how to predict intervention effects and reason counterfactually, equipping them with essential tools for answering causal questions across various fields.

Prose complexity
10/10

Vibe

InformativeIntellectualComplex

Genres

Mathematics Science

Authors

J
Judea Pearl

Judea Pearl is a leading figure in the field of artificial intelligence and the author of The Book of Why. His work focuses on causality and its role in understanding the world, making complex ideas accessible to a broad audience.

N
Nicholas P. Jewell

Nicholas P. Jewell is an author focused on statistical methods, particularly for public health and epidemiology. His notable works include "Causal Inference in Statistics" and "Statistics for Epidemiology." Jewell's books provide clear, practical guidance on complex statistical concepts for students and professionals in the field.