Recent content by macca1994

  1. M

    Classical definition of probability & kolmogorovs axioms

    oh okay, so you prove that it obeys the axioms by kolmogorov?
  2. M

    Classical definition of probability & kolmogorovs axioms

    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?
  3. M

    Proof of "If f(x) is Continuous, then |f(x)| is Continuous

    oh okay, i get it, thanks for the help
  4. M

    Proof of "If f(x) is Continuous, then |f(x)| is Continuous

    ah that makes sense and is very obvious, do you need to show that limit of lf(x)l is in fact lf(a)l or is that just obvious?
  5. M

    Proof of "If f(x) is Continuous, then |f(x)| is Continuous

    yeah, that's about the limit of my analysis knowledge, how would you use the ε,δ definition?
  6. M

    Proof of "If f(x) is Continuous, then |f(x)| is Continuous

    Ahh, yeah i get that, but can you not prove it without using composition of two functions?
  7. M

    Proof of "If f(x) is Continuous, then |f(x)| is Continuous

    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
  8. M

    Markov Chains and absorption probabilites

    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
  9. M

    Markov Chains and absorption probabilites

    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?
  10. M

    Markov Chains and absorption probabilites

    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?
  11. M

    Markov Chains and absorption probabilites

    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?
  12. M

    Markov Chains and absorption probabilites

    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?
  13. M

    Markov Chains and absorption probabilites

    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...
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