Probability, also known as "probability", reflects the probability of random events. Random events refer to events that may or may not occur under the same conditions.

For example, it is a random event to randomly select one from a batch of goods with genuine products and defective products, and "what is extracted is genuine products". Suppose a random phenomenon is tested and observed n times, in which event A appears m times, that is, its frequency is m/n. After a lot of repeated experiments, m/n is often closer to a constant (see Bernoulli's law of large numbers for details). This constant is the probability of the occurrence of event A, which is usually expressed by P (A).

Statistical definition

Under certain conditions, the experiment was repeated n times, where nA is the number of times that Event A occurred in n times. If with the gradual increase of n, the frequency nA/n gradually stabilizes around a certain value p, then the value p is called the probability of the occurrence of event A under this condition, and it is recorded as P (a) = P .. This definition is called the statistical definition of probability.

In history, Jacob Bernoulli is the first person to give a strict meaning and mathematical proof to the assertion that "when the number of experiments n increases gradually, the frequency nA is stable at its probability p".

From the statistical definition of probability, it can be seen that the numerical value p is a quantitative index to describe the possibility of event A under this condition.