Why P(A|B') not P(A)-P(A n B)?

  • Thread starter CAH
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In summary, the equations P(A|B') = P(AnB) / P(B') and P(A) - P(A n B) refer to different probability spaces and cannot be interchanged. The Venn diagram does not account for this distinction.
  • #1
CAH
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I know the equations that P(A|B') = P(AnB) / P(B')

But why isn't it P(A) - P(A n B)

See photo attachment

We know b didn't happen so isn't it just A minus the middle?
 

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  • #2
P(A)=P(A ∩ B )+P(A ∩ B')
P(A|B')=P(A ∩ B')/P(B')

Your version will hold only of P(B')=1.
 
  • #3
Specifically, [itex]P(A | B^{C}) := P(A) - P(A \cap B)[/itex] would still include B in the sample space. Given that B hasn't happen, you don't want B in the sample space.
 
  • #4
CAH said:
I know the equations that P(A|B') = P(AnB) / P(B')

But why isn't it P(A) - P(A n B)

In an expression for probability P(S), there are more things involved that the set S. The expression for a probability involves (perhaps implicitly) a particular "probability space". The expressions [itex] P(A|B') [/itex] and [itex] P(A \cap B') [/itex] both refer to the same set. However, they refer to different probability spaces. In the probability space for [itex] P(A|B') [/itex] no events in [itex] A \cap B [/itex] exist. In the probability space for [itex]A \cap B' [/itex] , events in [itex] A \cap B [/itex] may exist and may be assigned nonzero probabilities.

Your reasoning with the Venn diagram doesn't include the information about what sets are in the two different probability spaces.
 

1. Why is the formula for conditional probability P(A|B') not simply P(A)-P(A n B)?

The formula for conditional probability P(A|B') takes into account the fact that event B did not occur. This means that the sample space is reduced to only those outcomes where B did not happen, which affects the probability of event A occurring.

2. How does the formula P(A|B') account for the fact that event B did not occur?

The formula P(A|B') takes the probability of event A occurring in the reduced sample space of B' (B not occurring) and normalizes it by dividing it by the probability of B' occurring. This accounts for the fact that event B did not occur and adjusts the probability of event A accordingly.

3. Can you provide an example to illustrate why P(A|B') is not equal to P(A)-P(A n B)?

Assume you have a bag with 10 red and 10 blue marbles. If you draw a marble without replacement, the probability of drawing a red marble (event A) is 10/20 = 1/2. However, if you know that the marble drawn was not blue (event B'), the sample space is reduced to 10 red marbles, making the probability of drawing a red marble now 10/10 = 1. This is different from the formula P(A)-P(A n B), which would give a probability of 1/2 – 0 = 1/2.

4. When should I use the formula P(A|B') instead of P(A)-P(A n B)?

The formula P(A|B') should be used when you know that event B did not occur and you want to adjust the probability of event A accordingly. For example, in medical diagnosis, if a patient tests negative for a certain disease (event B'), the probability of them having the disease (event A) will be different from the overall probability of having the disease.

5. Are there any other situations where P(A|B') is used?

Yes, P(A|B') is used in many different fields such as genetics, finance, and engineering. It is commonly used in Bayesian statistics, where prior knowledge or information is used to update probabilities when new evidence is presented. It is also used in decision theory to calculate the expected utility of an action given that certain events have not occurred.

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