Computing the Probability of an Event: Learn It 4

Conditional Probability

So far we have computed the probabilities of events that were independent of each other. We saw that getting a certain outcome from rolling a die had no influence on the outcome from flipping a coin, even though we were computing a probability based on doing them at the same time. In this section, we will consider events that are dependent on each other, called conditional probabilities.

conditional probability

The probability the event [latex]B[/latex] occurs, given that event [latex]A[/latex] has happened, is represented as

 

[latex]P(B | A)[/latex]

 

This is read as “the probability of [latex]B[/latex] given [latex]A[/latex]”

 

Conditional Probability Formula

 

If Events [latex]A[/latex] and [latex]B[/latex] are not independent, then [latex]P(A \text{ and } B) = P(A) · P(B | A)[/latex]

It’s important to remember the conditional probability formula can also be written as [latex]P(A \text{ and } B) = P(B) · P(A|B)[/latex].

Probabilities can be expressed in fraction or decimal form. To convert a fraction to a decimal, use a calculator to divide the numerator by the denominator. Ex. [latex]\dfrac{19}{51}=19 \div 51 \approx 0.3725[/latex]
What is the probability that two cards drawn at random from a deck of playing cards will both be aces?