Instructor: Luc Bovens. This course meets T 4:00 – 6:30 p.m. in CW 213.
We start this course with David Spiegelhalter’s The Art of Statistics – How to Learn from Data (2019). This book is a popular introduction to statistics and data science. It contains historical and conceptual discussions of statistics and probability using minimal mathematics and includes many examples that are relevant to policy making. It will provide you with the tools for further readings. Subsequently students will choose a chapter that will be made available on Sakai from candidate books below, do a presentation and lead a discussion. Candidate books and topics are:
- The Psychology of Risk.
- Gerd Gigerenzer Risk Savvy 2015
- Evidence-Based Policy Making
- Nancy Cartwright and Jeremy Hardie Evidence-Based Policy: a Practical Guide to Doing it Better (2012);
- Risk and Decision-Making in Pregnancy and Child-Rearing
- Emily Oster Expecting Better: Why the Conventional Pregnancy Wisdom is Wrong and What You Really Need to Know (2013)
- Emily Oster Cribsheet: A Data-Driven Guide to Better, More Relaxed Parenting, From Birth to Preschool (2019)
- Risk in Politics and Economics
- Jeffrey Friedman War and Chance: Assessing Uncertainty in International Politics (2019)
- John Kay and Mervin King Radical Uncertainty (2020)
- Existential Risk
- Toby Ord The Precipice: Existential Risk and the Future of Humanity (2020);
- Thomas Moynihan X-Risk: How Humanity Discovered Its Own Extinction (2020)
- Nate Silver The Signal and the Noise—Why so many Predictions Fail—but some Don’t (2012; 2020);
- Philip E. Tetlock and Dan Gardner Superforecasting – The Art and Science of Prediction (2015)
Please note: This course counts toward the “value theory” distribution requirement for PHIL grad students.
Permission of the instructor is required to enroll in this course. PHIL grad students are exempt from this enrollment requirement.