aprokopiw - got it, thanks.The sequence of 3 heads makes it more likely that you've chosen the biased coin rather than the fair one, so the probability of another head is higher. As the sequence of observed heads gets longer, p(next toss is a H) tends to 1

<t>Additonal question - can you explain why you need to do this?'I need to take the last element of each of these coloumns and then generate a list of these 1000 entries. Use the frequency of these 1000 numbers and then plot those frequency on a Histogram 'why the last element of each column? How do...

<t>arunseshadri - make sure you use normrnd(), rather than rand(), if you're simulating a Wiener process! rand() gives you a uniform distribution, while you actually need a normal distribution. Run this code to see the difference:%uniform distuniform=rand(10000,1);hist(uniform,50)%normal dist:normal...

<t>I did the same thing, but it was at a smaller consulting firm where I was already working in the risk group (and it a few years). I was hired as a developer, and joined the firm with no understanding of risk management, but I did have a mathematical background (masters in physics). They wanted me...

Ummm.. well, what were you expecting, & what did you get?

<t>OK, perhaps I don't understand conditional probability well enough (highly likely), but I saw it this way:The three previous tosses don't affect the probability of the next toss. You either have a fair coin with p(H)=0.5, or a biased coin with p(H)=1.Since there are two fair coins and one biased,...

Ok, I shouldn't wade into something that I don't understand, but can't you sort the initial matrix main_set before you begin your decomposition? That way all the different permutations you list collapse to just one, which you can the decompose...J.