Conned Again, Watson! Cautionary Tales of Logic, Math, and Probability

Conned Again, Watson! Cautionary Tales of Logic, Math, and Probability

Conned Again, Watson! Cautionary Tales of Logic, Math, and Probability

Conned Again, Watson! Cautionary Tales of Logic, Math, and Probability

Synopsis

In Conned Again, Watson!, Colin Bruce re-creates the atmosphere of the original Sherlock Holmes stories to shed light on an enduring truth: Our reliance on common sense-and ignorance of mathematics-often gets us into trouble. In these cautionary tales of greedy gamblers, reckless businessmen, and ruthless con men, Sherlock Holmes uses his deep understanding of probability, statistics, decision theory, and game theory to solve crimes and protect the innocent. But it's not just the characters in these well-crafted stories that are deceived by statistics or fall prey to gambling fallacies. We all suffer from the results of poor decisions. In this illuminating collection, Bruce entertains while teaching us to avoid similar blunders. From "The Execution of Andrews" to "The Case of the Gambling Nobleman," there has never been a more exciting way to learn when to take a calculated risk-and how to spot a scam.

Excerpt

We all lose time and money every day to bad decisions. Often, we are not even aware of it. We continue in blissful ignorance, happy in the illusion that our native common sense is doing a good job of guiding us.

I was painfully reminded of this a few months ago. My friend Jo Keefe, a graduate student in decision theory at the London School of Economics, rang one afternoon.

"Colin," she said in dulcet tones, "I've got some questions here that should be fun for you. Professor X assigned a class exercise. We've each got to telephone half a dozen people we know and ask them what they think the chance of winning some simple bets would be. You're not supposed to work it out mathematically; just make a guess on the spot. Can I make you one of my panel?"

"Go ahead," I said confidently, thinking privately: "Ha! Think they can fool me, do they?"

The questions sounded reasonable enough, and I didn't hesitate to give rough answers. A week later, I discovered that one my guesses had been out by a factor of 10. It was little consolation to hear that Jo's other contacts, mostly Oxford mathematics graduates like herself, had been wrong by even larger multiples.

Now, of course Professor X is a fiend in human form, but the exercise was a timely reminder that we can all trip up on apparently simple choices, especially if probability or statistics . . .

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