1, different in nature: independent events may be mutually exclusive events or mutually exclusive events, but mutually exclusive events is definitely not an independent event. Independent event: whether event A (or B) occurs has no effect on the probability of event B(A). These two events are called independent events. The probability of mutually independent events occurring simultaneously P(A*B)=P(A)*P(B). Mutually exclusive events refers to two events that cannot happen at the same time.

2. The relationship is different: the number of events in mutually exclusive events can be two or more, and the opposing events are only for two events. The opposition between two events is a sufficient condition for their mutual exclusion, but it is not a necessary condition.

3. Different impacts: Independent events do not affect each other, but may occur at the same time. Mutually exclusive events refers to events that can't happen at the same time, that is, the intersection is empty, but they may affect each other (for example, if A happens, B will definitely not happen). As far as connection is concerned, independent events in mutually exclusive events may or may not be mutually exclusive, while mutually exclusive events is definitely not an independent event.

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Mutual exclusion is not independent, and independence is not mutually exclusive in the event? Answer? With events? b？ When the probability of occurrence is not zero. In general, this conclusion is not valid.

The independence of random variables is defined by the distribution function, while the irrelevance is only defined by the first moment (that is, mathematical expectation). Distribution function is a higher concept than moment. The distribution function can determine the moment, but the moment does not necessarily determine the distribution function. Of course, this is only an intuitive explanation.

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