Computational Statistics General statistics uses parameters (average, standard deviation etc.) to match the data and the distribution.
Hierarchical Bayes model uses the distribution of the parameters. Bayesian statistics is used to deal with this idea.
In general statistics, average and standard deviation are thought as summary of the data. So we used for Decision Making .
But hierarchical Bayes model is used to understand the distribution.
In general statistics, we need much data to get complicated moel.
But in hierarchical Bayes model, we do not need much data because this model uses data to modify hypothesis distribution.
We need to prepare good data and good hypothesis to use this strongness.
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