UNIVARSITY.ORG | 6. Monte Carlo Simulation
Interesting information about Universities
information about Universities, University, complete university guide, university league tables, which university should i go to, which university course is right for me, which university gives the most scholarship, iipm affiliated to which university, which university is best for mba distance education, which university is the best in the world,
37557
single,single-post,postid-37557,single-format-standard,ajax_leftright,page_not_loaded,,qode-title-hidden,qode-theme-ver-7.6.2,wpb-js-composer js-comp-ver-4.6.2,vc_responsive

28 Dec 6. Monte Carlo Simulation



MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
View the complete course: http://ocw.mit.edu/6-0002F16
Instructor: John Guttag

Prof. Guttag discusses the Monte Carlo simulation, Roulette

License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

VISIT ONE OF OUR SPONSORS. WITHOUT THEM, OUR WEBSITE WOULD NOT BE POSSIBLE.
MOST RECENT COMMENTS
35 Comments
  • Kirill Bezzubkine
    Posted at 08:25h, 28 December

    This man is really good at explaining the sense. There were no crazy sets of symbols though i got the essence of his explanation. The only downside of this is that it s NOT about monte carlo but more about some basic assumptions lying at the base of Monte Carlo

  • Steve Almond
    Posted at 08:25h, 28 December

    Hello, thank you for your lecture on Monte Carlo. I have a question, I don’t understand why it is better to run the simulation rather than just use the mean? For the roulette example, we’re providing the code the 1/36 probability and using a simulation to show that well win 1/36 times. But of course we know that already, and so why run the simulation? My question related to why I’m researching Monte Carlo. I have a real world problem where I am trying to forecast unplanned shutdowns for machinery. I have a detailed history of unplanned shutdowns for the past 10 years. Say I have 1005 machines and I have on average 7 breakdowns per month. Can I use Monte Carlo to forecast how many machines will breakdown per month going forward? Or should I just assume I’ll have 7 breakdowns per month? What would be the benefit of each? I’m happy to self learn, I’m hoping someone can point me in the right direction. Thank yoy

  • Wentao Qiu
    Posted at 08:25h, 28 December

    Ok, he is really good 33:45, how I hoped to have a prof. like him back in college.

  • Dobariya Hardik
    Posted at 08:25h, 28 December

    thanks, sir your lecture helps me allot

  • Sachin Dolta
    Posted at 08:25h, 28 December

    Here after reading Fooled by randomness by nasim taleb 🙂

  • ApiolJoe
    Posted at 08:25h, 28 December

    Probability of getting 26 reds in a row is 1 / 67 108 865 when p = 1/2 doesn't really seem possible, the denominator isn't even a multiple of 2 😛
    I guess the above probability was calculated with the real odds of a roulette and not those of a fair one.

  • Jordan Smith
    Posted at 08:25h, 28 December

    Good lecture overall but there is a bug in the code at 14:32 and 15:25 — playRoulette should instead print 100 * totPocket / (numSpins * bet).
    The output in his example only looks correct because `bet` is 1. If `bet` were 2 and `numSpins` were 1, it either prints "-200%" or "7200%" (obviously you can't lose more than 100% or win more than 3600%).

  • Zuheyr Alsalihi
    Posted at 08:25h, 28 December

    But this does not have anything at all with the MC method
    ….

  • Masihullah Hasanyar
    Posted at 08:25h, 28 December

    The state of idiots putting dislike for MIT content 🤣🤣🤣

  • Masihullah Hasanyar
    Posted at 08:25h, 28 December

    The state of idiots putting dislike for MIT content 🤣🤣🤣

  • William Mohr
    Posted at 08:25h, 28 December

    23:33 this should be corrected to –> if the parents are shorter than average, the children are likely to be taller than the parents ( not taller than average).

  • Lindsey Xiao
    Posted at 08:25h, 28 December

    1.25 speed

  • Abhishek Jaisingh
    Posted at 08:25h, 28 December

    The best way to explain variance formula! <3

  • Nas
    Posted at 08:25h, 28 December

    Thanks. It did help!

  • KingArthurVIII
    Posted at 08:25h, 28 December

    The failed slingshot attempt made the prof 300% more likable that he already was to begin with.

  • salman ahmed
    Posted at 08:25h, 28 December

    awesome

  • addi wei
    Posted at 08:25h, 28 December

    49:00 likelihood not equal probability

  • addi wei
    Posted at 08:25h, 28 December

    20:20 if the baseball hitter hit with a probability > .5 then of course it is probable he will hit one per each attempt

  • Petter Hemnes
    Posted at 08:25h, 28 December

    Great professor! A slight hiccup on 23:38; I believe he meant to say if the parents are both shorter than average it is likely that the child will be taller than their parents (not average).

  • Kenneth Mak
    Posted at 08:25h, 28 December

    Thank you, Prof. Guttag!

  • Anton Mochalin
    Posted at 08:25h, 28 December

    "A million is getting close to infinite" 😂

  • aem0117
    Posted at 08:25h, 28 December

    Good lecture, but I was expecting more Monte Carlo (Latin Hypercube, …) than elementary statistics.

  • Joe Donzi
    Posted at 08:25h, 28 December

    Roulette is not about spins , roulette is about being somewhere . This professor has obviously never actually been anywhere , never experienced anything. sorry , imho !

  • txlish
    Posted at 08:25h, 28 December

    oh, bring me back to Dr S.C. Arora , faculty of Mathematics from HansRaj College, Univ of Delhi lectures from '78, '79 -:)

  • apiwat tiger
    Posted at 08:25h, 28 December

    Oh my god. In my country there are none of teacher like this

  • ChannalMath
    Posted at 08:25h, 28 December

    lol! 33:50

    THAT's how you teach intelligent but sleep-deprived teenagers!

  • Lakshmi yes
    Posted at 08:25h, 28 December

    I still don't get how regression to means is consistent with the independence of events. Isn't the fact that the first 10 spins resulted in red (extreme) affect the next 10 spins (make it less likely to be as extreme)? Can someone pls explain that?

  • Kosteri x
    Posted at 08:25h, 28 December

    what a stupid video. It doesnt even use monte carlo.

  • ian park
    Posted at 08:25h, 28 December

    Truly a great professor.. we need more teachers and professors like him.

  • Nour Sayed
    Posted at 08:25h, 28 December

    Not what I was looking for, however very interesting and useful video, I will see more, thanks

  • G Kess
    Posted at 08:25h, 28 December

    Zoom out and quit trying to follow him as he paces. Thanks.

  • Trigz WoW Classic
    Posted at 08:25h, 28 December

    Check out my free advanced risk monte carlo simulator. Coded it by myself, would love to hear what you think: niclashummel.com/risk-simulator

  • Connor Rowe
    Posted at 08:25h, 28 December

    great video on statistics but i thought this was going to teach monte carlo simulations

  • mithil kulkarni
    Posted at 08:25h, 28 December

    Very good teacher..

  • M K
    Posted at 08:25h, 28 December

    do they get candy whenever they ask question? lol

YOU CAN NOW ADVERTISE WITH US. PLEASE CONTACT US FOR FURTHER INFORMATION IN REGARDS TO PRICING ETC.