Probabilistic Computation

There were different models and conceptualizations of probability as a concept in mathematics, ranging from purely objective, empirical, and deterministic to subjective, theoretical, and knowledge-centric. 

Bayesian probability was a probability that depended on the information that the person had knowledge of. 

For instance, if one were asked the probability of a tossed coin landing heads, one would say fifty percent. 

However, if one was informed that the tossed coin was one of five coin tosses, four of which yielded heads, then the answer would change.

After all, the probability of getting five heads in a row was three percent.

Frequentist probability determined a more empirically measurable form of probability that depended on a dataset of repeated trials to determine the empirical likelihood of an outcome based on the data. It would aim to determine the dataset of tossing a coin a thousand times in the above scenario.