Quote from: psterryl on September 27, 2014, 12:30:29 PM

Quote from: JorgeStolfi on September 27, 2014, 12:22:15 PM

Quote from: nioc on September 27, 2014, 08:18:25 AM

for the last 4 hrs, 240 minutes, 268 blocks were found.
How does this sound Jorge?

I understand that block finding is a Poisson process where the probability of finding a block in any small interval of time dt seconds long is dt/T where T is the mean time between blocks. Then, the probability of n blocks being found in an interval with length t is
exp(-t/T)*(t/T)^n/n!

In your example, t/T is 240 and we want the probability of n being 268 blocks or more. The answer is
exp(-240)*sum(k=268..oo 240^k/k!
That is not easy to compute, but for those range of values the distribution should be close to a Gaussian distribution with mean 240 and standard deviation sqrt(240). So we can instead compute the probability of a standard Gaussian variable (mean 0, variance 1) being greater than r = (268 - 240)/sqrt(240). I can't compute that right now, will do that later...

Forgive me if I'm wrong but would that analysis not require the assumption of constant hashrate/difficulty over the period considered? If there is a sharp rise or fall in hashrate over the period then you will end up with some very improbable results.

We have an increased hash rate recently.