Statistics Definitions > Conditional Probability
Conditional probability is the probability of one event occurring with some relationship to one or more other events. For example:
- Event A is that it is raining outside, and it has a 0.3 (30%) chance of raining today.
- Event B is that you will need to go outside, and that has a probability of 0.5 (50%).
A conditional probability would look at these two events in relationship with one another, such as the probability that it is both raining and you will need to go outside.
The formula for conditional probability is:
P(B|A) = P(A and B) / P(A)
which you can also rewrite as:
P(B|A) = P(A∩B) / P(A)
Conditional Probability Formula Examples
Watch the video, or read the examples below:
In a group of 100 sports car buyers, 40 bought alarm systems, 30 purchased bucket seats, and 20 purchased an alarm system and bucket seats. If a car buyer chosen at random bought an alarm system, what is the probability they also bought bucket seats?
Step 1: Figure out P(A). It’s given in the question as 40%, or 0.4.
Step 2: Figure out P(A∩B). This is the intersection of A and B: both happening together. It’s given in the question 20 out of 100 buyers, or 0.2.
Step 3: Insert your answers into the formula:
P(B|A) = P(A∩B) / P(A) = 0.2 / 0.4 = 0.5.
The probability that a buyer bought bucket seats, given that they purchased an alarm system, is 50%.
This question uses the following contingency table:
What is the probability a randomly selected person is male, given that they own a pet?
Step 1: Repopulate the formula with new variables so that it makes sense for the question (optional, but it helps to clarify what you’re looking for). I’m going to say M is for male and PO stands for pet owner, so the formula becomes:
P(M|PO) = P(M∩PO) / P(PO)
Step 2: Figure out P(M∩PO) from the table. The intersection of male/pets (the intersection on the table of these two factors) is 0.41.
Step 3: Figure out P(PO) from the table. From the total column, 86% (0.86) of respondents had a pet.
Step 4: Insert your values into the formula:
P(M|PO) = P(M∩PO) / P(M) = 0.41 / 0.86 = 0.477, or 47.7%.
Conditional Probability in Real Life
Conditional probability is used in many areas, including finance, insurance and politics. For example, the re-election of a president depends upon the voting preference of voters and perhaps the success of television advertising — even the probability of the opponent making gaffes during debates!
The weatherman might state that your area has a probability of rain of 40 percent. However, this fact is conditional on many things, such as the probability of…
- …a cold front coming to your area.
- …rain clouds forming.
- …another front pushing the rain clouds away.
We say that the conditional probability of rain occurring depends on all the above events.
Where does the Conditional Probability Formula Come From?
The formula for conditional probability is derived from the probability multiplication rule, P(A and B) = P(A)*P(B|A). You may also see this rule as P(A∪B). The Union symbol (∪) means “and”, as in event A happening and event B happening.
Step by step, here’s how to derive the conditional probability equation from the multiplication rule:
Step 1: Write out the multiplication rule:
P(A and B) = P(A)*P(B|A)
Step 2: Divide both sides of the equation by P(A):
P(A and B) / P(A) = P(A)*P(B|A) / / P(A)
Step 3: Cancel P(A) on the right side of the equation:
P(A and B) / P(A) = P(B|A)
Step 4: Rewrite the equation:
P(B|A) = P(A and B) / P(A)
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