Understanding Bayes' theorem
From the Bayesian point of view, probability measures the degree of likelihood that an event will occur. It is an inverse probability in the sense that from the observed frequencies, we obtain the probability. Bayesian statistics foresee the calculation of the probability of a certain event before carrying out the experiment; this calculation is made based on previous considerations. Using Bayes' theorem, by using the observed frequencies, we can calculate the a priori probability, and from this, we can determine the posterior probability. By adopting this method, the prediction of the degree of credibility of a given hypothesis is used before observing the data, which is then used to calculate the probability after observing the data.
Important Note
In the frequentist approach, we determine how often the observation falls in a certain interval, while in the Bayesian approach, the probability of truth is directly attributable to the interval...
