Conditional probability describes the likelihood of event when event is known to have occurred, calculated as for . The learner interprets as a restricted sample space, calculates conditional probabilities from tables, tree diagrams, or stated probabilities, distinguishes from , and identifies independence when conditioning does not change probability; this supports the multiplication rule for dependent events. Continuous distributions and measure-theoretic generalizations are outside this scope.
A conditional probability is the probability that event occurs when we know that event has occurred.
Use the formula
where means that both and occur.
Think of as the new, restricted sample space. Once is known, only the outcomes in matter.
A school surveys 100 students about club membership and whether they play a sport.
| Plays a sport | Does not play a sport | Total | |
|---|---|---|---|
| Club member | 18 | 12 | 30 |
| Not a club member | 42 | 28 | 70 |
| Total | 60 | 40 | 100 |
Find the probability that a student plays a sport, given that the student is a club member.
Let
We want , which means “the probability of playing a sport given club membership.”
Because we know the student is a club member, consider only the 30 club members. Thus,
There are 18 students who are both club members and play a sport. Therefore,
Therefore, the probability is
or .
The denominator is , not , because the information that the student is a club member restricts the sample space to the 30 club members.
Be careful not to reverse the events. For example,
which is different from . In general,
Click a topic below to practice the foundational skills you'll need, learn the steps, or master this skill
Earned ?