## Interest

on Oct 26, 2006

# Stumblers Who Commented On This Page

## Rofang

### Rofang

Kind of an interesting read.

## MegamanZX

### MegamanZX

:P I don't like statistics that much, but this proves to be interesting.

## xfx

### Xavier

That's weird... because for many years I've have "forced" coins tosses to my advantage by starting the toss on the opposite side from what I wanted it to land. Start heads, it lands tails (most of the time) and vice-versa.

## SmylesB

### Kyle

When does a hypothesis stop becoming common sense? I guess they still have to test the idea.

## toriture

### toriture

From the page: Preliminary analysis of the video-taped tosses suggests that a coin will land the same way it started about 51 percent of the time. "It's a gem-like example of what we know that isn't so," Diaconis says. Though a skeptic since childhood, he believed that "if you flipped a coin vigorously, it was going to be fair.

Reminded me of the book called "How We Know What Isn't So: The Fallibility of Human Reason in Everyday Life by Thomas Gilnovich". A great read if you liked the article.

## Arpana-INFJ

## Arpana

Magician-turned-mathematician uncovers bias in coin flipping

By ESTHER LANDHUIS

Persi Diaconis has spent much of his life turning scams inside out. In 1962, the then 17-year-old sought to stymie a Caribbean casino that was allegedly using shaved dice to boost house odds in games of chance. In the mid-1970s, the upstart statistician exposed some key problems in ESP research and debunked a handful of famed psychics. Now a Stanford professor of mathematics and statistics, Diaconis has turned his attention toward simpler phenomena: determining whether coin flipping is random. Could a simple coin toss -- used routinely to decide which team gets the ball, for instance -- actually be rigged?

Diaconis set out to test what he thought was obvious -- that coin tosses, the currency of fair choices, couldn't be biased. "Mathematicians are always doing that," he says. "You know, everybody knows it's true, and then we prove it. So what, right?"

Wrong. Diaconis had good reason to suspect that surprising truths lurk beneath common assumptions. He had uncovered them time after time. For example, people had long supposed that a few shuffles were sufficient to randomize a deck of cards -- until 1992, when Diaconis and Columbia University's David Bayer proved that thorough mixing requires seven shuffles.