I clearly understand what you're saying. Thanks for your time and detailed explanation.

> Standard error is a type of standard
> deviation - but not the type that we use in
> Risk, SCORE and optimal betting
> calculations. Standard error is used to
> measure the confidence that simmed results
> are correct while the standard deviation
> that we talk about is used to measure the
> confidence that your results will match
> expected results. The standard deviation we
> use, assuming flat-betting SD BJ, is about
> 1.1 irrespective of sample size. The
> standard error is the standard deviation in
> a determined statistic due to errors
> introduced by inadequate sample sizes.
> Standard error is the standard deviation of
> the measurement, not of what is being
> measured. If the sample size is infinite,
> there is no error and the standard error is
> zero. So, standard error (the standard
> deviation of sim results) reduces to zero
> with the sampling size and standard
> deviation (the standard deviation of BJ
> results) converges on the correct value (1.1
> in the case given above.)

> This goes to the heart of this thread. You
> need to play a certain number of hands to
> assure that you will be within a reasonable
> vicinity of expected results. N0 is normally
> in the tens of thousands of hands. But, to
> come up with the variables used in the
> calculation of N0, you must run a sim with a
> low enough standard error. That requires
> many millions of hands. To compare the
> effect on N0 of strategy changes requires a
> standard error that can only be met with
> billions of hands.