The Beta distribution is a continuous probability distribution defined on the interval [0, 1]. It is characterized by two shape parameters, often denoted as α (alpha) and β (beta), which determine the form of the distribution. This makes it versatile for modeling random variables that represent proportions or probabilities, such as the likelihood of success in a series of trials. Commonly used in Bayesian statistics, the Beta distribution can represent prior beliefs about probabilities before observing data. It is particularly useful in scenarios like A/B testing or project management, where outcomes are uncertain and need to be estimated based on limited information.