The answer depends on if and how the events depend on one another.
Things and numbers don't have probabilities. Situations and events that can happen have probabilities.
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.
They are not!
Yes
If the events are independent then you can multiply the individual probabilities. But if they are not, you have to use conditional probabilities.
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.
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.
Venn diagrams are useful for visualizing the relationships between different sets, making them a great tool for calculating probabilities. By representing events as circles that overlap, you can easily identify the probability of individual events, their intersections, and unions. For example, the area representing the intersection of two events A and B shows the probability of both events occurring simultaneously. This visual representation simplifies the calculation of probabilities, especially when dealing with multiple events and their relationships.
Yes. no its not its false :from Scott Powell
False
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.
They are both measures of the likelihood of specified events.