First of all, binomial distribution refers to the number of events in independent repeated experiments as a random variable, which obeys binomial distribution and is represented by B(n, p), where b is the symbol obeying binomial distribution, n represents the total number of events and p represents the probability of events. For example, a person can give you a typical example to help you understand. For example, he shot an arrow ten times, and every time he might hit or miss. Every archery is independent and repetitive, so it is consistent with independent and repetitive experiments. Then, the number of archery as a random variable obeys binomial distribution, where B( 10, p) and 10 are the total number of experiments, and p becomes the success probability, that is, the probability of shooting each time.