An interesting gamble

1 min read

The other day I was walking on a street, along which there are a lot of booths where people play games to gamble. I stopped in front of one booth. The host was warm and we started to talk.

“How to play?”, I asked.

“Well, simple.” He explained, “You pay $10 to play once. Then you toss a coin until you get a ‘head’ and the game is over. If you get a ‘head’ in the first toss, then I will pay you $1; if in the 2nd toss, I will pay you $2; 3rd I will pay you $4; … and nth I will pay 2^(n-1) dollars.”

“Interesting!” I then started to calculate if this game is fair to me. I needed to calculate the expected return from this game. If it’s larger than $10, then I win; otherwise I will lose. So what is the expected return?

The probability to get ‘head’ in the first toss is 1/2, 2nd time 1/4 and so on. So the expected return is 1×1/2 + 2×1/4 + 4×1/8 + … = 1/2 + 1/2 + 1/2 + 1/2 + … and the sum is infinity!

My return is infinity! And it’s much larger than $10 dollars. For sure I will play. I might become a millionaire today. I count my money in my wallet and I have $100.

“I am in!”, I told the host.

“Good decision.”, He similed.

Then I started to play. The first game I was unlucky. I got the head in the first toss. But it’s the risk I have to take to become a millionaire. So I keep playing.

Before I knew I already spent all my $100! I only won about $50. But at this point nothing could stop me from becoming a millionaire. So I keep playing until I lost all my money.

I was very disappointed, but I was more confused. The expected return is infinity, but why did I lose money? Did I make a mistake in the calculation?


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也许我偶尔还是会想他 偶尔难免会惦记着他 就当他是个老朋友啊 也让我心疼也让我牵挂 只是我心中不再有火花 让往事都随风去吧 所有真心的痴心的话 仍在我心中 虽然已没有他 上大学的时候,不知道为什么我们
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One Reply to “An interesting gamble”

  1. Hi,
    funny story!
    Generally, street gamblers are great mathematicians in their field. You got this experience a little expensive.
    The chance to retrieve your entrance fee was 1/32.

    Thank you for your website. I enjoy it. Thank you again for the SVM method and good examples.

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