Why - A Guide to Finding and Using Causes
Paperback Engels 2015 1e druk 9781491949641Samenvatting
Can drinking coffee help people live longer? What makes a stock’s price go up? Why did you get the flu? Causal questions like these arise on a regular basis, but most people likely have not thought deeply about how to answer them.
This book helps you think about causality in a structured way: What is a cause, what are causes good for, and what is compelling evidence of causality? Author Samantha Kleinberg shows you how to develop a set of tools for thinking more critically about causes. You’ll learn how to question claims, identify causes, make decisions based on causal information, and verify causes through further tests.
Whether it’s figuring out what data you need, or understanding that the way you collect and prepare data affects the conclusions you can draw from it, Why will help you sharpen your causal inference skills.
Specificaties
Lezersrecensies
Inhoudsopgave
1. Beginnings: Where do our concepts of causality and methods for finding it come from?
-What is a cause?
-How can we find causes?
-Why do we need causes?
-What next?
2. Psychology: How do people learn about causes?
-Finding and using causes
-Blame
-Culture
-Human limits
3. Correlation: Why are so many causal statements wrong?
-What is a correlation?
-What can we do with correlations?
-Why isn’t correlation causation?
-Multiple testing and p-values
-Causation without correlation
4. Time: How does time affect our ability to perceive and reason with causality?
-Perceiving causality
-The direction of time
-When things change over time
-Using causes: It’s about time
-Time can be misleading
5. Observation: How can we learn about causes just by watching how things work?
-Regularities
-Probabilities
-Simpson’s paradox
-Counterfactuals
-The limits of observation
6. Computation: How can the process of finding causes be automated?
-Assumptions
-Graphical models
-Measuring causality
-Now what?
7. Experimentation: How can we find causes by intervening on people and systems?
-Getting causes from interventions
-Randomized controlled trials
-When n=you
-Reproducibility
-Mechanisms
-Are experiments enough to find causes?
8. Explanation: What does it mean to say that this caused that?
-Finding causes of a single event
-Explanation with uncertainty
-Separating type and token
-Automating explanation
-Causality in the law
9. Action: How do we get from causes to decisions?
-Evaluating causal claims
-From causes to policies
-Chapter 10Onward: Why causality now?
-The need for causality
-Key principles
-A well-stocked toolbox
-The need for human knowledge
Appendix A: Notes
Index
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