Some Classical Statistical Applications

We dedicate this second block to some statistical applications. We start with the problem of estimating a rate considering two cases: (a) the sample size is known, and (b) it is unknown. As already known, if the parameters are assumed to be random we get a Bayesian method to analyze this problem. Some interesting dependencies of the parameters will be discovered. The second example is the Pearson correlation example, in which this statistic is considered as a random variable, instead of a deterministic value. This allows us to answer the problem of finding the Pearson correlation of a model by means of a density function instead of a point or confidence estimate, which goes further beyond than the classical statistics.