The probability formula is as follows:
1, classical probability: p (a) = number of basic events contained in a/total number of basic events = m/n;
If a random test contains limited unit events and the possibility of each unit event is equal, then this random test is called Laplace test, and the probability model under this condition is called classical probability model.
2. Geometric probability: P(A)= the length of the region that constitutes event A/the length of the region that consists of all test results;
If the probability of each event is only proportional to the length of the event area (area or volume or degree), such a probability model is called geometric probability model, which is called geometric probability model for short.
3. Conditional probability: P(A|B)=Nab/Nb=P(AB)/P(B)=AB, and the number of basic events involved/b;
Conditional probability refers to the probability that event A occurs under the condition that event B occurs. Conditional probability is expressed as: P(A|B), which is read as "the probability that A occurs under the condition that B occurs". If there are only two events, A and B, then P(A|B)=P(AB)/P(B).
In the formula, P(AB) is the joint probability of event AB, P(A|B) is the conditional probability, that is, the probability of A under the condition of B, and P(B) is the probability of event B. ..
4. Bernoulli probability: pn (k) = cn * p k
Bernoulli probability model is a probability model based on independent repeated experiments and satisfying binomial distribution. Its basic characteristics are:
① ? Do experiments repeatedly under a set of fixed conditions.
② ? There are only two results in each test: whether the event occurs or not.
③ ? In each experiment, the probability of the same event is the same.
④ ? The results of repeated tests are independent of each other.
Introduction to probability:
Also known as probability, probability or probability and possibility, it is the basic concept of mathematical probability theory, a real number between 0 and 1, and a measure of the possibility of random events. The number representing the probability of an event is called the probability of the event. It is a measure of the possibility of random events and one of the most basic concepts of probability theory.
People often say how sure someone is to pass the exam and how likely something is to happen. These are examples of probability. However, if the probability of an event is 1/n, it does not mean that the event must occur once in n events, but that the frequency of this event is close to the value of1/n.