Views : 7,705,801
Genre: Education
Date of upload: Jan 5, 2015 ^^
Rating : 4.962 (3,422/359,563 LTDR)
RYD date created : 2022-04-09T18:51:27.147498Z
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Top Comments of this video!! :3
I was shocked to see that no one took the bet easily.. because my father played this game with me various times and in that i was ready to lose my money(although i don't have much money).. but he wanted us to learn to take small risks.. from there I learned not to think about small losses much and it'd helped me in taking some decisions quite easily..and plus i feel more confident sometimes iykyk;)
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For those who are wondering, I convinced my interviewees that the bet was not a scam: they could inspect the coin, flip it themselves, use their own coin etc. I explained that the experiment was intended to explore their approach to risk. It was fear of losing $10, not distrust, that led them to decline the bet.
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I think it's not only about feeling about gains and losses, but also about what the relationship is of the money against your overal budget. I wouldn't take the bet if I only own 10 dollars, but easily accept it if I had 1000. Also, I wouldn't probably accept a bet of a random stranger because you probably have something fishy to do: no one gives away free money.
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A little extra math for anyone interested.
The long term expected value was hinted on in the video by saying that over 100 bets, you expect to win $500, with a 1/2300 chance of losing money. To explain this better you have to understand the relationship between expected value and variance (or standard deviations).
In his 10 vs 20 bets, the player's expected value is +$5 per bet. The standard deviation of each bet is $15, that is to say the player's expectation is $5 +/- $15.
Now, in the long term, expectations are linearly proportional whereas the standard deviations are proportional to the square root of the number of trials.
So for 100 bets, the player's expectation is +100*$5 (+$500). The standard deviation is sqrt(100)*$15, or $150.
One standard deviation away from the mean encompasses roughly 2/3 of all possible outcomes. Therefore the player after 100 bets, has a 2/3 chance of being up between $350 and $650.
Apply that math even farther, say 1,000,000 bets.
Expectation = $5,000,000
Standard Deviation = sqrt(1,000,000)*$15 = $15,000.
As the sample size grows, the standard deviation becomes a smaller and smaller proportion of the expected value.
This is the math that card counters, casinos, and even stock brokers rely on to make money.
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@Mewws
4 years ago
"i need half a million views" 4.2 Million views later
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