Compare 2 algorithms by statistics Let's suppose we have two different processes, each generating some amount of money $M$ every second.
$$0 \leq  M \leq 1000$$
We run each process for $50\%$ of available time.
The question is how to compare the productivity (in money; per second) of these two processes if there is no information about "random noise" in every process? The only information about each process we have is a log-file: what $M$ was generated at every second.

You have two samples - one from each method - with equal sample sizes (and big enough I assume) and you want to see which method generates statistically better results. This is a standard methodology with a confidence interval for the difference of means or a hypothesis testing again for the difference of means. Of course the result will at some significant level. 
The mean and the variances will be calculated from the sample, so do not worry about this "noice". The sample variance will take care of it.
