Conditional probability is the likelihood of an event occurring given that another event has already occurred. It is denoted by P(A|B), which is the probability of event A occurring given that event B has already occurred.
The formula for conditional probability is:
P(A|B) = P(A ∩ B) / P(B)
Where P(A ∩ B) is the probability of both event A and event B occurring, and P(B) is the probability of event B occurring.
Let's consider an example to understand conditional probability better. Suppose we have a bag containing 3 red balls and 2 green balls. If we draw a ball from the bag without replacement, what is the probability of drawing a green ball given that the first ball drawn was red?
We can use the formula for conditional probability to solve this:
P(Green|Red) = P(Green ∩ Red) / P(Red)
Since we are drawing without replacement, the probability of drawing a green ball after drawing a red ball is:
P(Green ∩ Red) = (2/4) * (3/5) = 6/20
P(Red) = 3/5
Therefore, the conditional probability of drawing a green ball given that the first ball drawn was red is:
P(Green|Red) = (6/20) / (3/5) = 6/12 = 1/2
Here are some key points to remember when studying conditional probability:
By mastering conditional probability, you will be able to analyze and understand the likelihood of events occurring in various situations, making it a valuable skill in many fields, including mathematics, statistics, and decision-making.