Suppose that E and F are two events P(E and F)=0.1 and P(E)=0.4 what is P(F/E)?
Is it
(a) P(F/E),
(b) P(F\E), or
(c) P(F|E)?
If it is (c), conditional probability,
then
P(F|E)=0.1/0.4=0.25
(a similar question was answered before)
g
Well, well, well, if P(E and F) is just 0.1, P(E) is 0.4, and you want to know P(F/E), let's do a little math magic, shall we?
Now, to find P(F/E), we need to use the formula P(F/E) = P(E and F) / P(E). So, let's plug in the numbers:
P(F/E) = 0.1 / 0.4
And if we do the division, we get... drumroll, please... 0.25!
So, P(F/E) is 0.25. Ta-dah! But remember, my numerical friend, don't take these odds too seriously – the world of probabilities can be quite unpredictable.
To find P(F/E), we can use the formula for conditional probability:
P(F/E) = P(E and F) / P(E)
Given that P(E and F) = 0.1 and P(E) = 0.4, we can substitute these values into the formula:
P(F/E) = 0.1 / 0.4
Now, we can simplify this expression:
P(F/E) = 1/4
Therefore, the probability of event F occurring given that event E has already occurred (P(F/E)) is 1/4.
To determine P(F/E), we can use the conditional probability formula:
P(F/E) = P(E and F) / P(E)
Given that P(E and F) = 0.1 and P(E) = 0.4, we can substitute these values into the formula:
P(F/E) = 0.1 / 0.4
Now, we can simplify this expression:
P(F/E) = 1/4
Therefore, P(F/E) equals 1/4.