Don't understand this conditional probabillity example

In summary, the conversation is about the calculation of P(B|A') for question c) in example 2. There is confusion about the value of P(B n A'), with one person believing it should be 0.15 instead of the stated 0.2. They ask for clarification on why it is 0.2. The other person agrees with the confusion and suggests that based on the diagram and their interpretation of the numbers, it should be 0.15. They thank the other person for their input.
  • #1
thisischris
26
1
At the bottom of the page (example 2) for question c) P(B|A').

They say P(B n A') = 0.2. But surely it is (B while not A) which in my mind should be 0.15.

Can somebody tell why it is 0.2?
 

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  • #2
thisischris said:
At the bottom of the page (example 2) for question c) P(B|A').

They say P(B n A') = 0.2. But surely it is (B while not A) which in my mind should be 0.15.

Can somebody tell why it is 0.2?

If the diagram is correct, and if my interpretation of the various numbers there is correct, it should be 0.15, as you want.

RGV
 
  • #3
Thank you!
 

What is conditional probability?

Conditional probability is the likelihood of an event occurring given that another event has already occurred. It is calculated by dividing the probability of the two events occurring together by the probability of the first event occurring.

How is conditional probability represented mathematically?

Conditional probability is represented using the notation P(A|B), which reads as "the probability of event A given that event B has already occurred." It is calculated using the formula P(A|B) = P(A ∩ B) / P(B), where P(A ∩ B) is the probability of both events A and B occurring together and P(B) is the probability of event B occurring.

What is the difference between conditional probability and joint probability?

Conditional probability refers to the likelihood of an event occurring given that another event has already occurred, while joint probability refers to the likelihood of two events occurring together. Conditional probability is calculated using the formula P(A|B), while joint probability is calculated using the formula P(A ∩ B).

How is conditional probability used in real-world situations?

Conditional probability is used in many fields, including science, economics, and medicine. It can be used to predict the outcomes of experiments, determine the likelihood of a disease given certain symptoms, and make decisions based on past events.

What are some common misconceptions about conditional probability?

One common misconception is that the probability of two independent events occurring together is always equal to the product of their individual probabilities. However, this is only true if the events are truly independent. Another misconception is that P(A|B) and P(B|A) are always equal, but this is only true in certain cases, such as when A and B are independent events.

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