A continuous probability distribution describes the probabilities of a continuous random variable, which can take any value within a given range. Unlike discrete distributions, where outcomes are distinct and countable, continuous distributions represent outcomes that can be measured, such as height or temperature. The total area under the curve of the distribution equals 1, indicating that the probability of the variable falling within a specific interval can be calculated. Common examples of continuous probability distributions include the normal distribution, uniform distribution, and exponential distribution. Each of these distributions has unique properties and applications, making them useful in various fields such as statistics, finance, and engineering. Understanding these distributions helps in modeling real-world phenomena and making informed decisions based on data.