Chance is a more fundamental conception than causality.And that's what Mlodinow has been proving, as he takes the reader on a road trip through the history of the development of modern techniques of statistical analysis, with some detours into personal reminiscence along the way. Starting from the concept of randomness, and moving through the basic principles of probability, the development of statistical explanations, and the law of large numbers, Mlodinow wears his learning lightly, and expresses it well. His explanations of the theory behind technical concepts like the law of large and small numbers, standard deviation, and variance are clear.
Human beings like to identify patterns in events, but our intuition often fails us. Seeing patterns where there were really just random events can result in large-scale shared illusions: Mlodinow cites the late 19th century craze for seances as an example. He discusses the availability bias -- the tendency to give available memories extra weight -- in simple, memorable terms, and shows how details that fit our mental picture add credibility to a scenario. He does the same thing with confirmation bias, the tendency to search for a way to prove that an idea is correct, while ignoring ambiguous or contradictory evidence. Mlodinow gently takes the reader to his conclusion that in random variation there may be patterns, but the patterns are not always meaningful. And then he offers some useful ways of overcoming our natural inclination to error:
1. Remember that chance events can produce patterns.
2. Question perceptions and theories.
3. Spend as much time looking for evidence that you are wrong as you spend looking for evidence that you are right.I've discussed these concepts before, but they're worth repeating. And Mlodinow takes a theoretical approach, while remaining completely accessible to the general reader. It's a fascinating book, well worth reading.
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