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Why : a guide to finding and using causes /
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: W...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol :
O'Reilly,
2015.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Copyright; Table of Contents; Preface; Chapter 1. Beginnings; What is a cause?; How can we find causes?; Why do we need causes?; What next?; Chapter 2. Psychology; Finding and using causes; Perception; Inference and reasoning; Blame; Culture; Human limits; Chapter 3. Correlation; What is a correlation?; No correlation without variation; Measuring and interpreting correlation; What can we do with correlations?; Why isn't correlation causation?; Multiple testing and p-values; Causation without correlation; Chapter 4. Time; Perceiving causality; The direction of time.
- When things change over timeUsing causes: It's about time; Time can be misleading; Chapter 5. Observation; Regularities; Mill's methods; Complex causes; Probabilities; Why probability?; From probabilities to causes; Simpson's paradox; Counterfactuals; The limits of observation; Chapter 6. Computation; Assumptions; No hidden common causes; Representative distribution; The right variables; Graphical models; What makes a graphical model causal?; From data to graphs; Measuring causality; Probabilistic causal significance; Granger causality; Now what?; Chapter 7. Experimentation.
- Getting causes from interventionsRandomized controlled trials; Why randomize?; How to control; Who do results apply to?; When n=you; Reproducibility; Mechanisms; Are experiments enough to find causes?; Chapter 8. Explanation; Finding causes of a single event; When multiple causes occur; Explanations can be subjective; When did the cause happen?; Explanation with uncertainty; Separating type and token; Automating explanation; Causality in the law; But-for causes; Proximate causes; Juries; Chapter 9. Action; Evaluating causal claims; Strength; Consistency (repeatability); Specificity.
- TemporalityBiological gradient; Plausibility and Coherence; Experiment; Analogy; From causes to policies; Context; Efficacy and effectiveness; Unintended consequences; Chapter 10. Onward; The need for causality; Key principles; Causation and correlation are not synonymous; Think critically about bias; Time matters; All experimentation is not better than all observation; A well-stocked toolbox; The need for human knowledge; Appendix A. Notes; Chapter 1. Beginnings; Chapter 2. Psychology; Chapter 3. Correlation; Chapter 4. Time; Chapter 5. Observation; Chapter 6. Computation.
- Chapter 7. ExperimentationChapter 8. Explanation; Chapter 9. Action; Chapter 10. Onward; Bibliography; Index; About the Author.