Tool for generating statistics from random draws to define items with output gaps and / or affinities in order to make predictions.
Random Draw Statistics - dCode
Tag(s) : Statistics
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During a repeated draw, the elements have an identical probability of coming out, so by repeating the draw a large number of times there will be on average a similar number of appearances for each element. The draw statistics try to bring out the elements which are not in the average, and which, when the draw is repeated a large number of times, will have more or less chance of appearing according to the mathematical predictions.
The elements drawn most often are part of the TOP-n (with n an integer, TOP-3 for the first 3, TOP-10 for 10 etc.) and the elements least drawn are part of the FLOP-n.
The output deviation is a statistic highlighting the difference between the observed number of appearances and the expected number of appearances of an element.
Example: During a heads or tails draw (therefore with 2 possibilities), after 10 draws, heads appeared 7 times and tails 3 times, but, on average, they should have appeared 5 times. The deviation is therefore +2 for heads and -2 for tails.
The law of larges is a mathematical property that equates the probability of an eventuality with the frequency of its occurrence. Thus based on a sufficiently large sample (going to infinity, hence the name of the law of large numbers), the average and the expectation converge to the same value.
In practice, it is illusory to apply this law on samples of a few tens or hundreds of draws to make predictions.
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Cite as source (bibliography):
Random Draw Statistics on dCode.fr [online website], retrieved on 2023-09-30,