One event does not affect the outcome of the other event.
The outcome of one event affects the outcome of another event.
Example
Flipping a coin and rolling a number cube.
Flipping a coin and then in the case of heads rolling a number cube and in the case of tails spinning a spinner.
Probability
P(AandB)=P(A)* P(B)
P(AandB)=P(A)* P(BfollowingA)
Now, a magazine rack contains 22 magazines in total.
5 sports magazines
7 news magazines
10 fashion magazines We know that after a magazine is chosen, it is not replaced. Next, a second magazine is chosen at random. This is an example of dependent events because the outcome of the first draw affects the possible outcomes of the second draw.
Let's find the probability of randomly choosing two fashion magazines. Because these events are dependent, this probability is equal to the product of the probability that a first magazine is about fashion and the probability that a second magazine is about fashion if one fashion magazine was already chosen.
P(two fashion) = P(first fashion)* P(second fashion)
We can start with the first probability. Because we have 10 fashion magazines and 22 magazines in total, the probability that a first magazine will be about fashion is 10 22.
P(two fashion)=10/22* P(second fashion)
After the first draw, we have 9 more fashion magazines and 21 magazines in total. This means that the probability of choosing the second fashion magazine is 9 21.
P(two fashion)=10/22* 9/21
Let's evaluate the product!
