The answer depends on whether or not the events are independent.
The probability of flipping one coin and getting tails is 1/2. In order to find the probability of multiple events occurring, you find the product of all the events. For 3 coins the probability of getting tails 3 times is 1/8 because .5 x .5 x .5 = .125 or 1/8.
Multiply the possible outcomes of the events in the disjoint events
It depends on whether or not the events are independent.
you find the probability
Things and numbers don't have probabilities. Situations and events that can happen have probabilities.
Divide the number of events that can happen a certain way by the number of all possible events.
The probability is 35/36.
Yes, a joint probability quantifies the likelihood of two or more events occurring at the same time. It is typically represented as ( P(A \cap B) ) for two events A and B, signifying the probability that both events happen together. Joint probabilities are fundamental in statistics and probability theory, especially in understanding the relationships between multiple random variables. They can be calculated using the multiplication rule if the events are independent or through conditional probabilities when they are not.
Two or more events are commonly referred to as "events" or "multiple events." In probability theory, they can also be described as "joint events" or "compound events," especially when considering their interactions or combinations. Additionally, in various contexts, terms like "occurrences" or "happenings" may be used to denote multiple events.
No, there isn't just one way of computing the probability of dependent events. One common method is to use the formula ( P(A \cap B) = P(A) \times P(B|A) ), where ( P(B|A) ) is the conditional probability of event B given that event A has occurred. Another approach involves constructing a probability tree or using joint probability tables, especially when dealing with multiple dependent events. The choice of method often depends on the context and the complexity of the events involved.
They are "events that have the same probability". Nothing more, nothing less.
Independent events with a probability of zero