IFA.tv - A Random Walker, Probability Machine, Galton Board, Quincunx



Take the Risk Capacity Survey and discover an appropriate portfolio for you: http://ifarcs.com - Visit IFA: http://ifa.com - More Videos: http://ifa.tv - Hebner Model: http://hebnermodel.com - Index Funds: The 12-Step Recovery Program for Active Investors: http://indexfundsbook.com - Complete the Retirement Analyzer: http://ifa.com/ra -- Call 888-643-3133 - http://IFAfacebook - http://IFAtwitter.com The Fair Price Simulator: An explanation of how random beads falling through an assortment of pins, in the pattern of a quincunx, looks like monthly returns of IFA Index Portfolio 100 over 50 years, ending 2008. See http://ifa.com/portfolios/p100/ - IP100 is a simulated index portfolio, with data going back to Jan 1928. - The machine was named Francis, in honor of Sir Francis Galton who first created such a machine in 1873. (see http://www.ucl.ac.uk/museums/galton/statistics/quincunx.html ). Also see http://en.wikipedia.org/wiki/Bean_machine and http://en.wikipedia.org/wiki/Normal_distribution . Video is narrated by Mark Hebner. Also see http://www.ifa.com/portfolios/p100/#9 , also see Chart number 10 on that page. From Wiki: In statistics, a random process is a repeating process whose outcomes follow no describable deterministic pattern, but follow a probability distribution, such that the relative probability of the occurrence of each outcome can be approximated or calculated. For example, the rolling of a fair six-sided die in neutral conditions may be said to produce random results, because one cannot compute, before a roll, what number will show up. However, the probability of rolling any one of the six rollable numbers can be calculated, assuming that each is equally likely. IFA.tv provides webcasts explaining the investing strategies of IFA.com and Mark Hebner's book, Index Funds: The 12-Step Recovery Program for Active Investors, with Foreword by Nobel Laureate Harry Markowitz. See hard cover here: http://www.IndexFundsBook.com ; the iBook here: http://IndexFundsiBook.com ; the Kindle edition here: http://IndexFundsKindle.com ; and the Nook edition here: http://IndexFundsNook.com.

Comments

  1. I think that it is accurate because "Most" events will follow a pattern, as in "Most" people will eat lunch around the same time, "Most" (the average) people will get 8 hours of sleep at night, make a certain amount of money in a given profession... but an outlier may not, they are represented by the random balls falling to the sides. Nature tends to follow the path of least resistance, and even though humans think they are "unique" we also follow this path for the most part.
  2. So an electronically managed account will do as well as a managed one? Great way to cut fees and costs! Go for it!
  3. Isn't the pattern due to the dropping of the balls in the center? What if you truly dropped them randomly? Some people claim it would be the same but there's no video to prove it…
  4. as random as finance / ecology ? 
  5. So that's what randomness looks like!
  6. I think the fact is that most folks don't want to admit that their lives and the things around them are complete and random chance. Thus, they must seek a cause.
  7. For those of you who don't know, even if you Dropped them on one side or the other, they would still fall to the middle. The pegs randomize the pattern.

    However, it is not a "random" distribution. Rather it is a normal distribution. 

    The point of the machine is to demonstrate that if a process is sufficiently randomized, then eventually, it will assume a normal distribution.
  8. People seem to not realise what random means.
    YES, the beads are more likely to end up in the centre, BUT them going towards the centre is in no way guaranteed.
    And you'll find that the beads will neatly follow a binomial distribution, which depending on the parameters can be approximated using the normal distribution.


    There are more kinds of random than just uniform distributions you guys.
  9. To me it looks like the tendency for the balls landing toward the center has something to do with the fact that they are funneled toward the center as they drop.
  10. Wow! Neat!
  11. Called a Gaussian distribution. main kinda thing of statistics
  12. Now I definitely have a better understanding of the Central Limit Theorem. Thanks to modern day technologies that make all these educational videos available!
  13. amazing
  14. @expatinasia62 Stock market returns are independent variables. The R Squared of First Day Returns vs Next Day Returns on 14,634 daily returns is 0.0052.
  15. @clipper721 You are wrong. For large number of experiments (large n) Bi(n,p) can be approximated to the Normal distribution N(np;np(1-p)) . Hence the bell shaped curve.
  16. @IndexFundsAdvisors ok thanks
  17. @gtacrusher123 The base can be taken off at the back and we can take out beads as they drop down a channel.
  18. @MrMSGMAIL The machine has a timer that controls the length each cycle of beads falling. It has another timer that can be set between 1 min and 60 minutes and initiates each cycle of beads going through the pins.
  19. @sfsTrader The beads only drop in at one point (centre) and can only travel left or right for a certain distance due to the depth of the drop (there only thirteen rows). So the maximum deviation in one direction is thirteen. This is not a truly random test, it is a machine that has been designed to describe a bell shaped curve, and a bell shaped curve is exactly what you would expect to get if you measure a phenomena over a period of time. So what is your point?
  20. @equilshift Just thought I might let you know that even the greatest minds that ever lived have struggled over this, and will continue to struggle over it for generations to come. (Indeed, eliminating the randomness "inherent" in our understanding of quantum mechanics was Einstein's white whale, he spent most of his academic career fruitlessly striving to eliminate the need for chance in our description of the universe.)


Additional Information:

Visibility: 133283

Duration: 4m 19s

Rating: 311