Bayesian Analysis with Python

Probabilities and uncertainty

While Probability Theory is a mature and well-established branch of mathematics, there is more than one interpretation of what probabilities are. To a Bayesian, a probability is a measure that quantifies the uncertainty level of a statement. If we know nothing about coins and we do not have any data about coin tosses, it is reasonable to think that the probability of a coin landing heads could take any value between 0 and 1; that is, in the absence of information, all values are equally likely, our uncertainty is maximum. If we know instead that coins tend to be balanced, then we may say that the probability of a coin landing is exactly 0.5 or may be around 0.5 if we admit that the balance is not perfect. If now, ...