No cheating on your red math workbook!
You multiply together their individual probabilities.
There is no secret: the procedures are well studied. However, it is important to know whether the events are independent or dependent.
They are not!
Things and numbers don't have probabilities. Situations and events that can happen have probabilities.
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.
You multiply together their individual probabilities.
There is no secret: the procedures are well studied. However, it is important to know whether the events are independent or dependent.
They are not!
This statement is true. The outcome results can be represented on a tree diagram which will allow people to view the compound event.
Things and numbers don't have probabilities. Situations and events that can happen have probabilities.
Yes
The answer depends on if and how the events depend on one another.
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.
Yes. no its not its false :from Scott Powell
False