I've seen in some probability theory books that the classical definition of probability is a probability measure, it seems fairly trivial but what is the proof for this? Wikipedia gives a very brief one using cardinality of sets. Is there any other way?
I have seen this theorem in a few books, but none of them give proofs, it says
if f(x) is a continuous function then lf(x)l is a continuous function. What is the proof of this because i don't really understand why this holds, thanks
I think i finally get it, so probability of 0 A's is equal to
(2/3)*(3/5)*(1/2) which is the probability of selecting a B each time
Then follow the same method for 1 A taking into account whether you chose the A first, second or third? I hope that's right
i really don't understand the probabilities of getting to the other states, do i not need to also consider what the other cell will contain or is that irrelevant?
oh is that standard binomial? so probability of going from state 1 to 0 would be (2/3)^3 which is 8/27 then do the same for the other states? or am i missing something?
how do i calculate the entries though, that's where I'm stuck at the moment, i know of course the lines for starting in state 0 and 3, but have no clue about 1 or 2, once i know that the rest of the question becomes fairly trivial, could you push me in the right direction?
So is the probability of say reaching state 1 from state 2 1/5 from the number of possible combinations of the daughter cell or am i going about this the wrong way?
Homework Statement
Could someone please help me with this question?
A single-celled organism contains N particles, some of which are of type A, the others of
type B . The cell is said to be in state i , where 0<=i<=N if it contains exactly i particles
of type A. Daughter cells are formed...