Thank you mturmon. that was super insightful. so if read this correctly (and the theorem) is ok to stop as long as the stopping is not dependent on any other variable (like results of the experiments or time). correct?
Typically, in an SLRT for a series of independent trials, you compute a running sum of likelihood terms (accumulating as you go) and then at some point you stop if the sum goes above one line or below another line. The separation between the lines tells you how much variability is "allowed" in the partial sums.
There are more general conditions than deciding in advance. The relevant theory in that case is the sequential likelihood ratio test (http://en.wikipedia.org/wiki/Sequential_probability_ratio_te...).
Typically, in an SLRT for a series of independent trials, you compute a running sum of likelihood terms (accumulating as you go) and then at some point you stop if the sum goes above one line or below another line. The separation between the lines tells you how much variability is "allowed" in the partial sums.