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<blockquote data-quote="bramadan" data-source="post: 353492" data-attributes="member: 1064">You guys should listen to 2WS-Steve he is probably the best game theorist in gaming this side of Johnatan Tweet. And also entirely correct in this issue. I liked the Bayes' theorem explanation best and if noone minds I would like to put it in a bit more layman's terms.Sigil is wrong on a very basic assumtion and that is a common assumption in proability which states that independent states are equally probable. If we had no information at all it would be the case and we would only have 25% chance for each of MM, MF, FM and FF combinations.However, *with prior information* provided by the picture things change and we have to ask ourselves what is the likelyhood that a person who certanly has a son falls into each either of the categories and it would be:MM - 50%MF - 25%FM - 25%FF - 0%the categories are not equivalent anymore because prior information has put bias into the way probabilities are allocated. It is kind of like betting on the outcome on two dice if I do not know any of the dice then the best odds I can give at the result being 12 are 1:36. If I know that one of the dice has fallen on 6 the odds of a 12 change to 1:6 (odds of 11 change from 1:18 to 1:6 etc...) Simmilarily if you count M as a 1 and F as 0 chance of total being 2 if one &quot;die&quot; is known to be 1 is 1:2 as opposed to 1:4 if both dice are unknown. Equal probabilty assumption is realy usefull and is used left and right in statistics but is only valid without prior information.</blockquote>

[QUOTE="bramadan, post: 353492, member: 1064"] You guys should listen to 2WS-Steve he is probably the best game theorist in gaming this side of Johnatan Tweet. And also entirely correct in this issue. I liked the Bayes' theorem explanation best and if noone minds I would like to put it in a bit more layman's terms. Sigil is wrong on a very basic assumtion and that is a common assumption in proability which states that independent states are equally probable. If we had no information at all it would be the case and we would only have 25% chance for each of MM, MF, FM and FF combinations. However, *with prior information* provided by the picture things change and we have to ask ourselves what is the likelyhood that a person who certanly has a son falls into each either of the categories and it would be: MM - 50% MF - 25% FM - 25% FF - 0% the categories are not equivalent anymore because prior information has put bias into the way probabilities are allocated. It is kind of like betting on the outcome on two dice if I do not know any of the dice then the best odds I can give at the result being 12 are 1:36. If I know that one of the dice has fallen on 6 the odds of a 12 change to 1:6 (odds of 11 change from 1:18 to 1:6 etc...) Simmilarily if you count M as a 1 and F as 0 chance of total being 2 if one "die" is known to be 1 is 1:2 as opposed to 1:4 if both dice are unknown. Equal probabilty assumption is realy usefull and is used left and right in statistics but is only valid without prior information. [/QUOTE]

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