2
Generating Posterior Distributions with the Binomial Distribution
In This Chapter
Understanding the Binomial Distribution
Understanding Some Related Functions
Bayesian analysis makes use of a variety of tools that are needed for special situations; for example, the Metropolis algorithm and a type of Metropolis algorithm called Gibbs sampling. But you can count on most instances of Bayesian analysis to depend on three structures: the prior distribution, the data (also termed likelihood), and the posterior distribution. This chapter discusses how you can make use of the binomial distribution to generate these structures.
Unfortunately, more than one name is used for each of these ...
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