Cause, Effect, and Everything in Between
An Introduction to Causal Inference
- Publisher's listprice GBP 16.99
-
8 116 Ft (7 730 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 812 Ft off)
- Discounted price 7 305 Ft (6 957 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
8 116 Ft
Availability
Not yet published.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher OUP USA
- Date of Publication 8 November 2025
- ISBN 9780197801789
- Binding Paperback
- No. of pages152 pages
- Size 206x142x15 mm
- Weight 159 g
- Language English 700
Categories
Short description:
Cause, Effect, and Everything in Between introduces readers to causal inference: the science of cause-and-effect. Using examples and case studies, Aboozar Hadavand provides an accessible introduction to the fundamental concepts and methodology of causal inference. By the end of the book, readers are equipped to interpret and assess causal claims in scientific research and political arguments, thus able to make better-informed decisions.
MoreLong description:
A practical guide to understanding the science of cause-and-effect for everyday decision-making.
In Cause, Effect, and Everything in Between, Aboozar Hadavand provides an easy-to-read and non-technical foundation to causal inference, especially for readers without a strong background in math and statistics. Rather than using statistical equations and mathematical theory, Hadavand focuses on developing readers' ability to analyze causal questions through a causal perspective. Using relatable examples, including the myth of the Swimmer's Body Illusion, the relationship between sleep apnea and growing a beard, and the relationship between smoking and dementia, Hadavand simplifies complex causal ideas.
The book starts by defining the fundamental concepts of causality, such as causal questions, causes, and effects. It then explores different types of causal inference problems, graphical tools for expressing causality, the shortcomings of randomized trials, and methods for inferring causality from observational data. Further, Hadavand debunks common misconceptions and teaches readers to differentiate between correlation and causation at a deep level by simplifying the concept of confounding bias and causal graphs. A concise and accessible introduction to causal inference that also includes end-of-chapter case studies with answers, this book equips readers to understand and critique scientific findings involving causal claims.
Table of Contents:
Preface
What Is Causality?
The Causal Framework
Causal Graphs and Causal Paths
Causal Inference Using Interventional Data
Causal Inference Using Observational Data
Quasi-Experimental Methods
A Framework for Evaluating Causal Studies
Causal Case Studies
Answers to End-of-Chapter Questions
Index
