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The Drunkard's Walk

The Drunkard's Walk

Leonard Mlodinow
2008
T2 252 pages · about 4h 12m to read Open Librarygoodreads

Summary

Mlodinow, a physicist, wrote an accessible book on randomness and probability, combining the history of the mathematics with evidence that people reason about it badly.

The historical thread runs from Cardano's early work on gambling odds through Pascal and Fermat's correspondence, Bernoulli's law of large numbers, Bayes and the problem of inverse probability, Laplace, Gauss and the normal distribution, and the development of statistics. Mlodinow explains each concept through the problem its originator was trying to solve.

The psychological thread reports the standard findings on probabilistic reasoning: the conjunction fallacy, where a specific conjunction is judged more probable than one of its components; base rate neglect, illustrated with medical testing where a positive result on an accurate test for a rare condition usually indicates no condition; the availability heuristic; the misunderstanding of conditional probability shown by the Monty Hall problem and by the prosecutor's fallacy; and the tendency to find patterns in random sequences, including the clustering illusion and the hot hand.

The applied argument concerns how much of observed success is randomness. Mlodinow examines mutual fund manager records, corporate executive performance, film studio executives, wine ratings, publishing decisions and sports streaks, arguing in each case that the observed distribution of outcomes is consistent with chance operating on small underlying differences, and that our tendency to construct causal narratives after the fact makes randomness invisible.

The book covers ground also covered by Taleb and Kahneman. Some of the psychology studies cited come from literatures affected by replication problems since 2008, though the core probability findings have held. The treatment is introductory and a reader with statistical training will find little new.

Key takeaways 7

  1. A positive result on an accurate test for a rare condition usually indicates the absence of the condition, because the base rate dominates.
  2. People judge specific detailed scenarios as more probable than the general cases that contain them, which is logically impossible.
  3. Random sequences produce clusters and streaks that observers reliably interpret as patterns.
  4. Mutual fund manager records over typical measurement periods are consistent with chance operating on small differences in skill.
  5. Success in fields with high outcome variance is attributed to individual quality afterward, regardless of what produced it.
  6. Conditional probability is reversed routinely in legal and medical reasoning, which produces systematic errors with serious consequences.
  7. Constructing a causal narrative after an outcome makes the role of randomness invisible even to people who understand probability.

Who should read it

Readers who want an accessible introduction to probability and to the errors people make with it, particularly when assessing track records.

Who recommended it 1 · 1 direct

Similar books 6

Chosen by shared topics, the entries that hold them, and the people who recommended both.

Peter L. Bernstein · 1996

How people learned to measure risk, from early probability to portfolio theory.

“I think some of the books that are a must would be Peter Bernstein's book about risk, Against the Gods: The Remarkable Story of Risk.” — Charles de Vaulx

Source: De Vaulx naming Bernstein's book a must-read on risk

Recommended by: Charles de Vaulx, Jim Collins and 8 others

Douglas W. Hubbard · 2007

Calibration and the value of information applied to intangibles.

Recommended by: Julia Galef, Nick Ganju

Nate Silver · 2012

Why some forecasts succeed and most fail, from weather to earthquakes and economics.

Where it sits in the reference 3

Investment philosophy
Mental models
Mental models

Topics

Mathematics and StatisticsDecision MakingStatistics, probability and data