Difference between revisions of "Conditional probability"

Revision as of 12:05, 29 June 2024

Conditional probability is the probability of an event occurring, assuming that another event has already occurred. $P(B|A)$ is said as the probability of event B given A

Example

Let us say that 2 fair 6 sided dice are rolled and their face up values sum is 6. What is the probability that the face up value of the one dice is 2?

Solution

Let call the first dice $D_1$ and the second one $D_2$ . There are 5 ways for $D_1 + D_2 = 6$ and 2 of those ways (distinct) includes a 2. Therefore, our answer is $\frac {2} {5}$ .

Formula

The formula for conditional probability is $P(A \cap B) = P(A) \cdot P(B|A)$ where $P(B|A)$ represents the conditional probability. $P(B|A)$ is also said as the probability of event B occurring given event A occurs. $P(A \cap B)$ is the probability $P(A) \cdot P(B)$ .We can also represent $P(A|B)$ as $$ (Error compiling LaTeX. Unknown error_msg)P(A|B) = \frac {P(A \cap B)} {P(A)}

Different cases

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 ==Formula==
-The formula for conditional probability is <cmath>P(A \cap B) = P(A) \cdot P(B|A)</cmath> where <math>P(B|A)</math> represents the conditional probability. <math>P(B|A)</math> is also said as the probability of event B occurring given event A occurs. <math>P(A \cap B)</math> is the probability <math>P(A) \cdot P(B)</math>.
+The formula for conditional probability is <cmath>P(A \cap B) = P(A) \cdot P(B|A)</cmath> where <math>P(B|A)</math> represents the conditional probability. <math>P(B|A)</math> is also said as the probability of event B occurring given event A occurs. <math>P(A \cap B)</math> is the probability <math>P(A) \cdot P(B)</math>.We can also represent <math>P(A|B)</math> as <math></math>P(A|B) = \frac {P(A \cap B)} {P(A)}
 ==Different cases==
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