For example, when I flip a coin, I have a 1/2 chance of getting head, and the same chance at getting tails. With that theory, if I toss a coin 50 times, I should get 25 heads, and 25 tails.
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However, I did 3 rounds of 50 coin flips, with results of:
1. 28 heads, 22 tails
2. 27 heads, 23 tails
3. 27 heads, 23 tails.
I assumed that perhaps the coins weren’t “true”. Maybe the sides are waited different, maybe I tossed with different height/force each time. So I went virtual, and switched to having a computer roll a dice.
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I should have a 1/6 chance at rolling a number between 1-6. So 60 rolls, should have each number come up 10 times. But in practice my results were:
1. 14
2. 9
3. 8
4. 13
5. 6
6. 10
So how come practice/reality, doesn’t align with theory, even when we take human error out of the equation?
In: 34
They do align, perfectly. Just as we can calculate the probability that you will get heads or tails if you flip a coin once, we can use the binomial distribution formula to calculate the probability of various outcomes if you flip a coin 50 times. For example, the probability of getting 25 heads and 25 tails is about 11%, the probability of getting 27 heads is about 10%, and the probability of getting 28 heads is about 8%. So these are not surprising outcomes at all. If you got 49 or 50 heads, that would be an extremely surprising outcome and would suggest that something was wrong.
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