Understanding Independent Probability | Concepts and Examples

Independent Probability

Independent probability refers to the probability of two or more events occurring which are not influenced by one another

Independent probability refers to the probability of two or more events occurring which are not influenced by one another. In other words, the outcome of one event does not affect the outcome of the other event.

To understand independent probability, we need to understand the concept of events. An event is simply something that can happen. For example, rolling a dice and getting a 4 is an event. Flipping a coin and getting a heads is also an event.

When two events are independent, the probability of both events happening is equal to the product of their individual probabilities. For example, let’s consider rolling a dice and flipping a coin. The probability of rolling a 4 is 1/6, and the probability of getting a heads on the coin flip is 1/2. Since these events are independent, the probability of both events occurring (rolling a 4 and getting heads) is (1/6) * (1/2) = 1/12.

To summarize:
– Independent probability refers to the probability of multiple events occurring where the outcome of one event does not affect the outcome of the other event.
– The probability of independent events occurring together is found by multiplying the individual probabilities of each event.

It is important to note that independence is not always the case in real-world scenarios. Events can be dependent on each other, which means the outcome of one event affects the probability of the other event occurring.

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