Very simple proof of P(A) > P(B)

  • Thread starter ChickenChakuro
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In summary, using the given information, we can prove that P(A) is always greater than P(B) by showing that P(A) - P(A∪C) > P(B) - P(B∪C) and P(A) - P(A∪~C) > P(B) - P(B∪~C). This can be further simplified to P(A) - P(A|C) > P(B) - P(B|C) and P(A) - P(A|~C) > P(B) - P(B|~C). By using the fact that P(A|B) = P(A∩B)/P(B), we can see that the bracketed term is greater than
  • #1
ChickenChakuro
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Homework Statement


Given that P(A|C) > P(B|C) and P(A|[tex]\bar{C}[/tex]) > P(B|[tex]\bar{C}[/tex]), prove that P(A) > P(B)

Homework Equations


How do I write the proof formally?

The Attempt at a Solution


This seems to me intuitively obvious. There are only two sample spaces, either C occurs or does not occur. In both instances, A has a higher chance of ocurrence than B. So how can P(A) NOT be always greater than P(B)? I have been told that P(A) > P(B) can be proven mathematically. However I'm not good at formal proofs. Can anyone help me write this out in mathematical form?

Many thanks!
 
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  • #2
I'd try something like this:
P(A) = P(B) [ P(A | B) / P(B | A) ]
What can you say about the bracketed term, possibly using that
[tex]P(A \mid B) = \frac{P(A \cap B)}{P(B)}[/tex]

Not guaranteed to work, but it might.
 
  • #3
Remember that [itex]P(A or B) = P(A) + P(B) - P(A and B)[/itex].
 
  • #4
I managed to work this proof down to P(A)-P(AUC)> P(B)-P(BUC) and P(A)-P(AU~C) > P(B)-P(BU~C) but I am not sure where to go from there!
 

1. What is the definition of P(A) > P(B)?

The statement P(A) > P(B) means that the probability of event A occurring is greater than the probability of event B occurring.

2. How is P(A) > P(B) proven to be true?

P(A) > P(B) can be proven using the basic rules of probability, such as the addition rule and the multiplication rule. It can also be proven using mathematical equations and logical reasoning.

3. What is the significance of P(A) > P(B) in scientific research?

P(A) > P(B) can be used to make predictions and draw conclusions in scientific research. It can also help determine the likelihood of a hypothesis being true based on the probability of certain events occurring.

4. Can P(A) > P(B) be applied to all situations?

No, P(A) > P(B) does not apply to all situations. It is specifically used in the context of probability and cannot be applied to other scientific concepts.

5. What are some real-life examples of P(A) > P(B)?

One example of P(A) > P(B) is the probability of flipping a coin and getting heads (event A) versus the probability of flipping a coin and getting tails (event B). Another example is the probability of rolling a higher number on a dice (event A) versus the probability of rolling a lower number (event B).

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