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The Causal Mindset Handbook : A Practical Guide to the Science of Cause and Effect for Evidence-Based Decision Making.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Gallea, Quentin.
Language:
English
Subjects (All):
Causation.
Decision making.
Physical Description:
1 online resource (212 pages)
Edition:
1st ed.
Place of Publication:
Birmingham : Packt Publishing, Limited, 2026.
Summary:
Make 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.
Contents:
Intro
Title Page
Copyright and Credits
Foreword
Contributors
Table of Contents
Preface
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Part 1: Why Causality?
Chapter 1: Understanding Causality and Its Importance
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Introducing causality
What is causality?
The big picture
Dumb data versus our limited perception
Visualizing cause and effect
Everything is multifactorial
Case studies
Case study 1: Cold showers and the immune system
Case study 2: Marketing campaign for energy sobriety
Case study 3: Air pollution and respiratory disease
Summary
Chapter 2: Causation versus Prediction
Why words matter: The thin terminology frontier
Different roles: Predictive inference (predictive AI) versus causal inference
Choosing between traditional ML and causal inference
A powerful collaboration: When causal inference allows you to measure the impact of predictive tools
Unification: Causal AI, an exciting, emerging new field
Case study 1: Cold showers and health
Case study 2: Energy sobriety campaign in Switzerland
Part 2: What Are the Main Challenges?
Chapter 3: Why Is It So Hard To Prove Causality?
Understanding the fundamental problem of causal inference
Exploring counterfactuals
Proving causality
Playing the causal detective game
Chapter 4: Beyond Correlation: The Main Culprits
Identifying confounders
Mediators and colliders
Non-classical measurement errors
Spotting reverse causation
External validity
Case studies.
Case study 1: Cold showers and the immune system
Part 3: What Are the Solutions?
Chapter 5: The Causal Mindset Framework
Learning about the Causal Mindset framework
Step 1: What is the proxy counterfactual?
Step 2: Is there something else?
Step 3: What is the direction of the bias?
Step 4: Refining and iterating
Step 5: Can we extrapolate?
The app
When to use the Causal Mindset framework
Understanding the importance of domain knowledge in causal inference
Step 1: What is the counterfactual?
Chapter 6: Randomized Experiment
Designing a credible experiment
Selecting a sample
Treatment allocation
Randomize everything that can be randomized
Placebo, nocebo, and blinding
Preventing contamination and spillovers
Non-compliance
Ethical considerations
Assessing randomized experiments' weaknesses
External validity in randomized experiments
Why statistics are essential for A/B testing
Randomization is not always possible
Suggested answer
Chapter 7: Quasi-Experimental Methods
Understanding identifying assumptions
Difference-in-differences
Identifying assumption for difference in differences
Difference-in-differences examples
Regression discontinuity design
Identifying assumption for RDD
How to validate the identifying assumption
RDD examples
Instrumental variables
Identifying assumptions for an instrumental variable
Examples of instrumental variables
Part 4: How to Deal with Imperfection
Chapter 8: Correct Answer, Wrong Question: The Importance of Choosing the Right Metrics
Answering the wrong question correctly
Misunderstood pathway
Misleading outcome extrapolation
Selecting the right metrics to measure what matters
Assessing and addressing behavioral bias
Case study 1: Cold Showers and the immune system
Chapter 9: Embracing Uncertainty
Chapter 10: Unlock Your Exclusive Benefits
Other Books You May Enjoy
Index.
Notes:
Description based on publisher supplied metadata and other sources.
Part of the metadata in this record was created by AI, based on the text of the resource.
ISBN:
1-80611-784-3
9781806117840
OCLC:
1573147306

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