Independent Event
When one event does not have an effect on another event
In probability theory, independent events are events that do not affect the probability of each other occurring. It means that the occurrence of one event does not impact the likelihood of the other event or events.
For example, if you roll a fair six-sided die, the outcome of each roll is an independent event. The probability of rolling a 6 on the first roll is 1/6, and the probability of rolling a 6 on the second roll is also 1/6 since the first roll does not affect the second roll.
Another classic example of independent events is flipping a coin. If you flip a coin once, the probability of getting heads is 1/2, and the probability of getting tails is also 1/2. If you flip the coin again, the first flip does not affect the probability of getting heads or tails in the second flip.
It is important to note that if events are not independent, they are dependent. Dependent events are events that affect each other, and their occurrence is interrelated. For example, if you draw a card from a deck and do not replace it before the second draw, then the second draw is a dependent event.
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