Conditional Probability Formula

The conditional probability P(A|B) is the probability of event A occurring given that event B has already occurred.

The Formula

P(AB)=P(A and B)P(B)P(A|B) = \frac{P(A \text{ and } B)}{P(B)}

When to use: If I know BB happened, what's the chance of AA? Updates probability with new info.

Quick Example

P(draw redalready drew one red)P(\text{draw red} \mid \text{already drew one red}) changes because there's one fewer red.

Notation

P(AB)P(A|B) reads 'the probability of AA given BB'; the vertical bar means 'given that' — it names the event you already know happened. P(AB)P(A \cap B) is the chance both happen, and P(B)P(B) is the new, smaller denominator (once BB is given, only BB's outcomes are left to count). P(AB)P(A|B) and P(BA)P(B|A) usually differ because they divide by different totals: with 12 sport, 8 music, 5 both, P(sportmusic)=5/8P(\text{sport}|\text{music}) = 5/8 but P(musicsport)=5/12P(\text{music}|\text{sport}) = 5/12.

What This Formula Means

The conditional probability P(AB)P(A|B) is the probability of event AA occurring given that event BB has already occurred.

If I know BB happened, what's the chance of AA? Updates probability with new info.

Formal View

P(AB)=P(AB)P(B)P(A|B) = \frac{P(A \cap B)}{P(B)} where P(B)>0P(B) > 0

Worked Examples

Example 1

medium
In a class of 3030 students, 1818 play soccer, 1212 play basketball, and 66 play both. If a student plays soccer, what is the probability they also play basketball?

Answer

P(BS)=13P(B \mid S) = \frac{1}{3}

First step

1
We need P(BS)=P(BS)P(S)P(B \mid S) = \frac{P(B \cap S)}{P(S)}.

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Example 2

hard
A test for a disease is 95%95\% accurate (true positive rate) with a 3%3\% false positive rate. If 1%1\% of the population has the disease, what is the probability a person who tests positive actually has the disease?

Example 3

medium
Of 200200 surveyed, 120120 own a dog and 8080 own a cat; 5050 own both. P(catdog)=?P(\text{cat}|\text{dog})=?

Common Mistakes

  • Dividing by the whole sample space — divide by P(B)P(B), the known condition, which shrinks the denominator.
  • Swapping P(AB)P(A|B) and P(BA)P(B|A) — read carefully which event is the 'given.'
  • Assuming independence to skip the formula — only set P(AB)=P(A)P(A|B)=P(A) if you have verified the events are independent.

Why This Formula Matters

Conditional probability is how reasoning updates with evidence — it powers medical test interpretation, Bayes' rule, and the formal definition of independence (P(AB)=P(A)P(A|B)=P(A)). Students who forget that the denominator becomes P(B)P(B) instead of 1 misread risk and overcount. Recognizing it by "Has some information already been revealed that shrinks the set of possible outcomes?" — rather than by familiar numbers — is what lets a student tell it apart from joint probability and independent events and reversed conditional p(ba)p(b|a) in a mixed problem set.

Frequently Asked Questions

What is the Conditional Probability formula?

The conditional probability P(AB)P(A|B) is the probability of event AA occurring given that event BB has already occurred.

How do you use the Conditional Probability formula?

If I know BB happened, what's the chance of AA? Updates probability with new info.

What do the symbols mean in the Conditional Probability formula?

P(AB)P(A|B) reads 'the probability of AA given BB'; the vertical bar means 'given that' — it names the event you already know happened. P(AB)P(A \cap B) is the chance both happen, and P(B)P(B) is the new, smaller denominator (once BB is given, only BB's outcomes are left to count). P(AB)P(A|B) and P(BA)P(B|A) usually differ because they divide by different totals: with 12 sport, 8 music, 5 both, P(sportmusic)=5/8P(\text{sport}|\text{music}) = 5/8 but P(musicsport)=5/12P(\text{music}|\text{sport}) = 5/12.

Why is the Conditional Probability formula important in Math?

Conditional probability is how reasoning updates with evidence — it powers medical test interpretation, Bayes' rule, and the formal definition of independence (P(AB)=P(A)P(A|B)=P(A)). Students who forget that the denominator becomes P(B)P(B) instead of 1 misread risk and overcount. Recognizing it by "Has some information already been revealed that shrinks the set of possible outcomes?" — rather than by familiar numbers — is what lets a student tell it apart from joint probability and independent events and reversed conditional p(ba)p(b|a) in a mixed problem set.

What do students get wrong about Conditional Probability?

The procedure for conditional probability is the easy part; the trap is dividing by the whole sample space. Asking "Has some information already been revealed that shrinks the set of possible outcomes?" first is what keeps a correct-looking calculation from being attached to the wrong concept.

What should I learn before the Conditional Probability formula?

Before studying the Conditional Probability formula, you should understand: probability, independent events.