Yes.
no its not its false :from Scott Powell
The Poisson distribution. The Poisson distribution. The Poisson distribution. The Poisson distribution.
In that case, the events are said to be independent.
What is the difference between dependant and independent events in terms of probability
Yes.
Add the probabilities of the two events. If they're not mutually exclusive, then you need to subtract the probability that they both occur together.
They are not!
Two events are said to be independent if the outcome of one event does not affect the outcome of the other. Their probabilities are independent probabilities. If the events are not independent then they are dependent.
To calculate the probabilities of compound events, you can use the multiplication rule or the addition rule, depending on whether the events are independent or mutually exclusive. The multiplication rule is used when the events are independent, and you multiply the probabilities of the individual events. The addition rule is used when the events are mutually exclusive, and you add the probabilities of the individual events.
If the events are independent then you can multiply the individual probabilities. But if they are not, you have to use conditional probabilities.
You multiply together their individual probabilities.
No, it is not.
Yes, when two probabilities are multiplied, it typically indicates a compound event, specifically in the context of independent events. This multiplication reflects the likelihood of both events occurring together. For instance, if you have two independent events A and B, the probability of both occurring is calculated by multiplying their individual probabilities: P(A and B) = P(A) × P(B). However, if the events are not independent, you would need to consider their relationship to determine the combined probability correctly.
There is no secret: the procedures are well studied. However, it is important to know whether the events are independent or dependent.
Two events are said to be independent if the result of the second event is not affected by the result of the first event. Some common ways to teach this are to perform simulations with coin flips.Students need to understand that if A and B are independent events, the probability of both events occurring is the product of the probabilities of the individual events.Students can predict and then observe probabilities of a fixed number of heads or tails.This lets then see the ideas in action.
The product rule states that the probability of two independent events occurring together is equal to the product of their individual probabilities. In genetics, the product rule is used to calculate the probability of inheriting multiple independent traits or alleles simultaneously from different parents.
When two probabilities are added together, the result represents the probability of either of the two events occurring, provided that the events are mutually exclusive (i.e., they cannot happen at the same time). If the events are not mutually exclusive, their combined probability would require adjustments to avoid double-counting the overlap. Thus, in the case of mutually exclusive events, the sum of their probabilities is a valid representation of a simple event.
To find the probability of a compound event, you can use the addition rule and the multiplication rule, depending on whether the events are mutually exclusive or independent. For mutually exclusive events, you add their individual probabilities. For independent events, you multiply their probabilities together. If the event involves both types, you may need to combine these rules accordingly. Always ensure to account for any overlaps or dependencies between the events.