CHAPTER 0 - Preface Flashcards
What has changed in the world according to the preface?
The world has changed in transformative ways with data and evidence being ubiquitous.
Why is competence in quantitative reasoning important for every educated person?
It is a fundamental responsibility of every educated human being and citizen.
What was the primary goal in writing ‘Thinking Clearly with Data’?
To provide students with the tools needed to be serious, thoughtful, and skeptical consumers of quantitative information.
What kind of courses were developed for teaching quantitative reasoning?
Courses aimed at students with little technical background, including university offerings and executive education courses.
What is the first part of the book focused on?
Establishing a shared language around correlation and causation.
Why is understanding correlation and causation important?
To comprehend why correlation doesn’t imply causation.
What are the two main concepts discussed in part 1 of the book?
- Correlation
- Causation
How does the book aim to keep readers engaged?
By telling stories and emphasizing ideas first before technicalities.
What is emphasized to avoid the memorization of technicalities?
Discussing ideas and their importance first.
What is the significance of familiarity with technical matters?
It is part of being a clear thinker.
What are the two types of errors to avoid when interpreting quantitative information?
- Misleading oneself about what quantitative information answers
- Confusing correlation with causation
What is the focus of part 2 of the book?
Using data and evidence to determine if a correlation exists.
What common mistake is explained in chapter 4?
Selecting on the dependent variable.
What is covered in chapter 5?
Measuring correlations and a graphical explanation of regression.
What concept does chapter 6 introduce?
Statistical significance and hypothesis testing.
What issues are discussed in chapter 7?
P-hacking, publication bias, and related issues.
What topic does chapter 8 address?
Reversion to the mean and its relation to the replication crisis.
What does part 3 of the book focus on?
Causal inference and its importance for decision-making.
What key concept does chapter 9 explain?
Why correlation does not imply causation.
What research designs are introduced in chapters 11-13?
- Randomized experiments
- Natural experiments
- Regression discontinuity
- Difference-in-differences designs
What does chapter 15 warn against?
Fooling oneself into thinking quantitative information answers a different question.
What does chapter 16 discuss?
Measurement, external validity, and extrapolation.
What fundamental limits are addressed in chapter 17?
The limits of quantitative analysis in informing decision-making.
What is the target audience for this book?
Everyone interested in learning to think clearly about data, evidence, and quantitative reasoning.
