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[tex]P(B|A)=\frac{P(B\cap A)}{P(A)}[/tex]
Therefore:
[tex]P(A)=\frac{P(B\cap A)}{P(B|A)}[/tex]
  • An event is the result of a random experiment or a group of shared results.
  • It could be defined as every subset of a sample space because the sample space is a collection of all possible results of a random experiment.

When the event B is dependenting on event A,

[tex]\to \bold{P(B \cap A) \neq P(B)\times P(A)}\\\\[/tex]

When the event A comes before event B. So, the probability of B given A:

[tex]\to \bold{P(B|A)=\frac{P(B\cap A )}{P(A)}}[/tex]

Solving the value for the P(A):

[tex]\to \bold{P(A)=\frac{P(B\cap A)}{P(B| A)}}[/tex]

Therefore, the "[tex]\bold{P(A)=\frac{P(B\cap A)}{P(B| A)}}[/tex]" is correct.

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