**Epistemic Probabilism**, also known as **Subjective Probabilism**, is a philosophical position that views probability as subjective and related to an individual's beliefs or degree of belief about uncertain propositions or events. According to this perspective, probabilities represent the strength of an individual's beliefs rather than objective frequencies or propensities inherent in the events themselves.

## Variants[edit | edit source]

### Bayesianism[edit | edit source]

In Bayesian framework probabilities are treated as degrees of belief or degrees of uncertainty, rather than as objective frequencies. Bayesian inference involves updating beliefs based on new evidence, using Bayes' theorem to calculate the probability of a hypothesis given the available data. This approach is often contrasted with frequentist statistics, which emphasizes the objective measurement of frequencies and probabilities in repeated experiments.

Bayes' original definition of probability focused on the ratio between the value of an expectation that depends on an event and the value of the thing expected upon the event's occurrence. This definition is subjective and does not require repeated events, but it does require the event to be observable. Modern Bayesian statisticians have expanded on Bayes' original definition in various ways, but some argue that Bayes intended his results to be applied in a more limited fashion.

## Criticism[edit | edit source]

Critics of Bayesianism argue that it is limited by its reliance on subjective probabilities, and that it fails to account for the objective reality of the world. Additionally, Bayesianism has been criticized for its potential to lead to circular reasoning and for its inability to handle certain types of uncertainty, such as Knightian uncertainty, which involves situations where the probability of an event cannot be assigned at all.

## Further Information[edit | edit source]

### Wikipedia[edit | edit source]