Persi Diaconis explains Randomness
Why Cross Validated Stack Exchange recommends it
Stats Stack Exchange (Cross Validated) users link it as a vivid illustration that coin tossing is a deterministic process whose apparent randomness reflects limited information, and that a skilled tosser can control the outcome.
Recommended by 1 people across 1 different months, 2014 to 2015.
What it is
A short clip from the Against All Odds series in which Stanford statistician and mathematician Persi Diaconis explains that randomness depends on how much information you have. He argues that with perfect knowledge an event is not random, and shows a demonstration of tossing a fair coin so it lands heads at will.
What people said
Recommends Glen_b · 2015-09 · Cross Validated Stack Exchange · on “Check whether a coin is fair”
Persi demonstrating the skill of tossing heads at will [this video] (link should go to the two minute mark; the relevant part goes for about a minute)
Cites Matt Brenneman · 2014-01 · Cross Validated Stack Exchange · on “Can a magician bias the result of a fair die?”
Some time ago, Persi Diaconis was discussing probability and made the point that the level of information a person possessed about an event played a role in his accessing probabilities. To illustrate this point, he did a very nice demonstration showing how a magician can toss a fair coin in such a way that he will always get heads. (See 2:10 in a video of Diaconis [this video] ) I am curious if this is possible using a fair die? TIA, Matt
Cites Glen_b · 2015-02 · Cross Validated Stack Exchange · on “Does 10 heads in a row increase the chance of the next toss being a tail?”
they are trying to assert that [...] if there have been 10 heads, then the next in the sequence will more likely be a tail because statistics says it will balance out in the end There's only a "balancing out" in a very particular sense. If it's a fair coin, then it's still 50-50 at every toss. The coin cannot know its past . It cannot know there was an excess of heads. It cannot compensate for its past. Ever . it just goes on randomly being heads or tails with constant chance of a head. If $n_H$ is the number of heads in $n=n_H+n_T$ tosses ( $n_T$ is the number of tails), for a fair coin, $n_H/n_T$ will tend to 1, as $n_H+n_T$ goes to infinity .... but the absolute discrepancy from equal num
Cites Tim · 2015-05 · Cross Validated Stack Exchange · on “Is tossing a coin a fair way of randomising a group into two groups?”
Yes, coin flip is truthfully random process. While it is possible to load a die, so that it favours certain outcomes, you cannot bias a coin (see paper by Andrew Gelman and Deborah Nolan [LINK] published in The American Statistician for further details). You can argue that coin toss is a deterministic process and in fact you can build a mathematical model that describes the process, however its outcome is random. For learning more on physics on coin toss check lectures by Santosh S. Venkatesh [LINK] on Probability course on Coursera.org where he describes the dynamics of coin toss in detail and provides an argument why it is truthfully random (Tableau 7), you can also check Keller's paper Th