Geometric distribution is a probability distribution that represents the number of trials needed to obtain a success in a Bernoulli experiment.
Bernoulli distribution is a simplified probability function where a random variable can have only two possible binary outcomes.
The posterior predictive distribution is a distribution for predicting future, unknown data values based upon the data currently available.
The conjugate prior is an initial probability assumption expressed in the same distribution type (parameterization) as the posterior probability or likelihood function.