The thrill and rush of possibly winning started to wear off after about the twentieth losing ticket. Each card had a couple of “Life” symbols on them, and every time you got a second you just dreamed of seeing the third one under the remaining graphite. However it never appeared and never will and it just kind of turned depressing. How could people put themselves through this humiliation and teasing every day of their lives?
The classic criticism of the lottery is that the people who play are the ones who can least afford to lose; that the lottery is a sink of money, draining wealth from those who most need it. Some lottery advocates . . . have tried to defend lottery-ticket buying as a rational purchase of fantasy—paying a dollar for a day's worth of pleasant anticipation, imagining yourself as a millionaire. But consider exactly what this implies. It would mean that you're occupying your valuable brain with a fantasy whose real probability is nearly zero—a tiny line of likelihood which you, yourself, can do nothing to realize. . . . Which makes the lottery another kind of sink: a sink of emotional energy. [via]
posted by Jasper Friendly Bear
on May 18, 2013 -
151 comments
Is Psychometric g a Myth? - "As an online discussion about IQ or general intelligence grows longer, the probability of someone linking to statistician Cosma Shalizi's essay
g, a Statistical Myth approaches 1. Usually the link is accompanied by an assertion to the effect that Shalizi offers a definitive refutation of the concept of general mental ability, or psychometric
g."
[more inside]
posted by kliuless
on Apr 11, 2013 -
113 comments
Bayesian analysis shows redshirts are not most likely to die on Star Trek:TOS. Although Enterprise crew members in redshirts suffer many more casualties than crew members in other uniforms, they suffer fewer casualties than crew members in gold uniforms when the entire population size is considered. Only 10% of the entire redshirt population was lost during the three year run of Star Trek. This is less than the 13.4% of goldshirts, but more than the 5.1% of blueshirts. What is truly hazardous is not wearing a redshirt, but being a member of the security department. The red-shirted members of security were only 20.9% of the entire crew, but there is a 61.9% chance that the next casualty is in a redshirt and 64.5% chance this red-shirted victim is a member of the security department. The remaining redshirts, operations and engineering make up the largest single population, but only have an 8.6% chance of being a casualty.
posted by Cash4Lead
on Feb 20, 2013 -
75 comments
The Nature of Computation -
Intellects Vast and Warm and Sympathetic: "I hand you a network or graph, and ask whether there is a path through the network that crosses each edge exactly once, returning to its starting point. (That is, I ask whether there is a 'Eulerian' cycle.) Then I hand you another network, and ask whether there is a path which visits each node exactly once. (That is, I ask whether there is a 'Hamiltonian' cycle.) How hard is it to answer me?" (
via)
[more inside]
posted by kliuless
on Dec 1, 2012 -
19 comments
Tails of the Unexpected: "Normality has been an accepted wisdom in economics and finance for a century or more. Yet in real-world systems, nothing could be less normal than normality. Tails should not be unexpected, for they are the rule." An eminently human-readable explanation of why normal models fail to describe the uncertainties of our abnormal world.
[more inside]
posted by ecmendenhall
on Jun 9, 2012 -
19 comments
An "Exciting Guide to Probability Distributions" from the University of Oxford:
part 1,
part 2. (Two links to PDFs)
posted by JoeXIII007
on Dec 15, 2011 -
17 comments
"So, if the probability of finding an egg with two yolks is 1/1000 - then to find the likelihood of discovering four in a row you simply multiply the probabilities together four times. One thousand to the power of four brings us to the grand total of one trillion...
If true that would mean the event that occurred in Jen's kitchen was a trillion-to-one event. But is it true? No is the short answer."
posted by Petrot
on Dec 10, 2011 -
38 comments
Measure-theoretic probability: Why it should be learnt and how to get started. The
clickable chart of distribution relationships. Just two of the interesting and informative probability resources I've learned about, along with countless other tidbits of information, from statistician
John D. Cook's
blog and his probability fact-of-the-day Twitter feed
ProbFact. John also has daily tip and fact Twitter feeds for
Windows keyboard shortcuts,
regular expressions,
TeX and LaTeX,
algebra and number theory,
topology and geometry,
real and complex analysis, and beginning tomorrow,
computer science and
statistics.
posted by grouse
on Dec 5, 2010 -
17 comments
The day after a senator from Illinois, is elected president, the Pick 3 lottery in Illinois
comes up 666. It's
happened before, notably in Pennsylvania (12 times, including one time as
part of a scam and once earlier this year,
in Maryland. Some are jokingly (I hope) calling him
the antichrist as a result. Others, namely numbers geeks like me, are spending their lunch hours looking up the history of lotteries drawing triple numbers and sharing it with MetaFilter.
posted by sjuhawk31
on Nov 6, 2008 -
70 comments
THE FOURTH QUADRANT: A MAP OF THE LIMITS OF STATISTICS by Nassim Nicholas Taleb. "In the following Edge original essay, Taleb continues his examination of
Black Swans, the highly improbable and unpredictable events that have massive impact. He claims that those who are putting society at risk are "no true statisticians", merely people using statistics either without understanding them, or in a self-serving manner.
posted by vronsky
on Sep 16, 2008 -
41 comments
On May 13, security advisories published by
Debian and
Ubuntu revealed that, for over a year, their OpenSSL libraries have had a major flaw in their
CSPRNG, which is used by
key generation functions in many widely-used applications, which caused the "random" numbers produced to be extremely predictable.
[lolcat summary] [more inside]
posted by finite
on May 16, 2008 -
81 comments
Experts can suck at predicting the future. Their intuitive sense of probability is no more developed than lay-people's. A classic experiment is to present two indistinguishable choices are presented, but with unequal probability of reward. Humans look for complex patterns, which don't exist, and preform quite poorly. Rats quickly recognize the choice with higher probability, and preform optimally.
posted by jeffburdges
on Dec 11, 2005 -
34 comments
Incredible -- but true coincidences are fascinating, and pleasing, to the psyche. I tend to agree with John Littlewood (a University of Cambridge mathematician) that "...in the course of any normal person's life, miracles happen at a rate of roughly one per month." In other words, statistically speaking, unusual coincidences are to be expected in a world teeming with billions of humans. Still, I find such coincidences stangely inspiring. More can be found
here.
posted by ember
on Jul 7, 2005 -
97 comments
The Logic of Diversity "A new book,
The Wisdom of Crowds [
..:] by
The New Yorker columnist James Surowiecki, has recently popularized the idea that groups can, in some ways, be smarter than their members, which is superficially similar to
Page's results. While Surowiecki gives many examples of what one might call collective cognition, where groups out-perform isolated individuals, he really has only one explanation for this phenomenon, based on one of his examples: jelly beans [
...] averaging together many independent, unbiased guesses gives a result that is probably closer to the truth than any one guess. While true — it's the
central limit theorem of statistics — it's far from being the only way in which
diversity can be beneficial in problem solving."
(Three-Toed Sloth)
posted by kliuless
on Jun 20, 2005 -
6 comments
"We plan to put Beauty to sleep by chemical means, and then we’ll flip a fair coin. If the coin lands Heads, we will awaken Beauty on Monday afternoon and interview her. If it lands Tails, we will awaken her Monday afternoon, interview her, put her back to sleep, and then awaken her again on Tuesday afternoon and interview her again. The (each?) interview is to consist of the one question : what is your credence now for the proposition that our coin landed Heads? When awakened (and during the interview) Beauty will not be able to tell which day it is, nor will she remember whether she has been awakened before. She knows about the above details of our experiment. What credence should she state in answer to our question?"
In light of the recent thread on the
Monty Hall problem, here's a probability puzzle that's even more mind-bending: the
Sleeping Beauty problem. Some people say the answer is
1/2. Some people say the answer is
1/3. Some people say there is
no answer.
Papers have been written which can't resolve this one.
posted by salmacis
on Jul 21, 2004 -
40 comments
Expect a miracle? Freeman Dyson on Littlewood's Law of Miracles: "...the total number of events that happen to us is about thirty thousand per day, or about a million per month. ...The chance of a miracle is about one per million events. Therefore we should expect about one miracle to happen, on the average, every month." From his review of book debunking the paranormal (whose views he isn't entirely willing to accept).
Via
Marginal Revolution
posted by Jos Bleau
on Jul 14, 2004 -
33 comments
What Are The Odds Against Hamlet? This wonderful piece, representative of British academia at its best, most tongue-in-cheek, inclusive and playful, still presents a problem which wasn't (probably can't be) solved. What are the odds that it could be taken seriously? Mathematicians and literary theorists enter at their peril. The rest of us can feel free!
posted by MiguelCardoso
on Feb 10, 2004 -
5 comments
