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In probability, once a distribution has been selected it is then necessary to estimate the values of its associated ''parameters'' in order to specify the particular distribution out of the family or class of distributions which differ only on the basis of the values of these parameters.
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In probability, once a model class has been selected it is then necessary to estimate the values of its associated ''parameters'' in order to specify that particular model out of all members of the model class which differ only on the basis of the values of these parameters.
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In [[Bayesian Probability]], parameters are estimated by computing the joint [[posterior distribution]] of the parameter set using [[Bayes Rule]].
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In [[Bayesian Probability]], the parameters are estimated from data by computing the joint [[posterior distribution]] of the parameters and the data using [[Bayes Rule]].
    
[[category:mathematics]]
 
[[category:mathematics]]
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