1. Strict definition of probability: E is a random test and S is its sample space. For each event A of E, assign a real number, which is denoted as P(A), which is called the probability of event A. Here, P () is a set function, and P () must meet the following conditions:
(1) Nonnegativity: for each event A, there is p (a) ≥ 0;
(2) Normality: for the inevitable event S, there is p (s) =1;
(3) Countable additivity: Let A 1, A2…… ...... become mutually incompatible events, that is, for i≠j, Ai∩Aj=φ, (I, J = 1, 2 ...), and then P (A/kloc. ..
Second, probability theory is a mathematics that studies randomness or uncertainty. More precisely, probability theory is used to simulate the situation that experiments will produce different results in the same environment. In nature and human society, there are a lot of random phenomena, and probability is a measure of the possibility of this phenomenon.