steve_bank
Diabetic retinopathy and poor eyesight. Typos ...
Then I am not sure you know what you are talking about. I am sure it is all very clear to yourself.I agree it poorly defined.
What does s1 and s2 not separated mean? In statistical terms do you mean correlated vs uncorrelated(random) variables?
Pa does bot make sense in the table. if s is a random variable with two staes and s1 s2 are continget on s then s1 + s2 has to equal 50%.
Please explain Swami.
Wrte out the probailty equations fr Pa and Pb in the tables.
I'm not sure what your questions are..
P(A|.) is the label for one row; substitute the column label for the dot to get P(A|S), P(A|not.S), P(A|S1), P(A}S2).
Thus P(A|S1) = 90% means that in Scenario S1, A is true 90% of the time. (Never mind which is cause and effect, if any. Treat it as a pure math exercise with the probabilities given.)
Note that the source code provided ensures exactly that and may answer other questions as well. See something like
case 1: // S_1Clue_A = (random() < 0.90 * RAND_MAX);(I'd intended that source code to be easy-to-read, but looking now I see it assumes familiarity with C and its random() library.)
In the other thread's example. S is the proposition that Sam committed a certain robbery. One detective divides S into two scenarios (Sam hired George as his getaway driver OR Sam drove himself). Other detectives do not consider the getaway at all, due to oversight or perhaps afraid it might confuse them further.
As you can see from the table, the clues are useless for the detectives who do NOT subdivide into two scenarios. Clue B for example might be that George has a good alibi on the day of the robbery.
There is little math here, just the same posts that ended up in Elsewhere on the other hread.
I will try and avoid this kind of OPs in the future.