Is the Probability Formula P(C∩G) = P(G)P(C|G) Correct?

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The formula P(C∩G) = P(G)P(C|G) is correct, as it reflects the definition of conditional probability, where P(C|G) represents the probability of event C occurring given that event G has occurred. The proposed alternative, P(C∩G) = P(C)P(C|G), is incorrect because it misinterprets the relationship between the events. In cases where C and G are independent, P(C|G) equals P(C), which aligns with the book's formula. Misunderstanding the notation may lead to confusion about the events' dependencies. Understanding these probability concepts is crucial for accurate calculations.
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Homework Statement



My book says that
P(C∩G) = P(G)P(C|G)

but shouldn't it be

P(C∩G)= P(C)P(C|G)

?


Homework Equations





The Attempt at a Solution

 
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princejan7 said:

Homework Statement



My book says that
P(C∩G) = P(G)P(C|G)

but shouldn't it be

P(C∩G)= P(C)P(C|G)
No. To see why, consider the case where ##C## and ##G## are independent. Then we expect ##P(C|G) = P(C)## and ##P(C \cap G) = P(C)P(G)##. That is consistent with the formula from the book, not your proposed formula.
 
princejan7 said:

Homework Statement



My book says that
P(C∩G) = P(G)P(C|G)

but shouldn't it be

P(C∩G)= P(C)P(C|G)

?


Homework Equations





The Attempt at a Solution


The book is correct. The definitionof conditional probability is
P(C|G) \equiv \frac{P(C \cap G)}{P(G)} \text{ if } P(G) \neq 0
Sometimes, however, we are given ##P(C|G)## and ##P(G)##; in that case we can get ##P(C \cap G)## by 'reversing' the formula above.
 
Last edited:
princejan7 said:
My book says that
P(C∩G) = P(G)P(C|G)

but shouldn't it be

P(C∩G)= P(C)P(C|G)
Perhaps you are misreading the notation. P(C|G) means the probability of the event C given that event G occurs. Maybe you read it as the other way around?
 
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