[MUSIC] The second key concept is the concept of event. We define an event E, like any sub-set of basic outcomes from the sample space. An event occurs if the results of the random experiment belongs to its basic outcomes. An event is said to be null if represents the absence of any basic outcome. We can have the intersection of events. Sometimes our interest focuses on the simultaneous occurrence of two or more events. In these cases, specific outcomes in both events occur simultaneously. This is true for outcomes that are contained in both events. If A and B are two events in the sample space S, their interaction indicates all basic outcomes in S that belong to both A and B. We can say that the intersection of A and B occurs if and only if both A and B happen. The expression we used to indicate the intersection of events is the joint probability of A and B. More formally, we say that given K events, E1, E2 up to EK. Their intersection E1, E2 up to EK, is the set of all basic outcomes that belong to every Ei, where i = 1, 2, up to K. We can hold so f, mutually exclusive events. This occurs when the event A and B, have no common basic outcomes. In case of mutually exclusive events, their interaction, Is said to be the empty set. This indicates that the A and B intersection has no members. More generally, we have that. The K events, E1, E2, up to EK are said to be mutually exclusive if every pair Ei, Ej, is a pair of mutually exclusive events. Finally, we can also have a union of events. If A and B are two events in the sample space S, the union of A and B constitutes the set of all basic outcomes in S that belong to at least one of these two events. Therefore, the union A and B occurs if and only if either A or B or both happen. More generally, given the K events, E1, E2, up to EK. The union E1, union E2 up to EK is the set of all basic outcomes belonging to at least one of these K events. [MUSIC]