How to calculate it...
The thoughts I brought up in my prior post pertain to approximation methods that help to simplify the estimation of standard deviation and variance over a period of time. If one has the time and necessity to do so, it can be calculated rather accurately.
A few weeks ago someone asked about figuring standard deviation without a simulation. I responded with the notion of executing a method utilizing the knowledge of frequency of advantage, or more ideally, true count, to determine the overall standard deviation for any spread. There's no reason this wouldn't work (assuming I was correct;-) for the variance, as variance itself is simply the square of the standard deviation.
Further research on this matter has uncovered that this methodology has been utilized by Michael Hall, as well as George C., so I'm pretty confident I was on the right track.
The following is an excerpt from Michael Hall's 1991 RoR article.
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III. George C. on the Ruin Formula
From "The Ruin Formula", by George C., Blackjack Forum, September 1988...
George shows how to compute variance, like so:
6 Decks Strip Rules w/DDAS, 75% Penetration
Advantage__Hands/Hour_______Bet Squared $__Product $
------------- --------------- ------------------ ---------------
__-3.4%_______1.0_______________10000______10000
__-2.9%_______2.0_______________10000______20000
__-2.4%_______3.0_______________10000______30000
__-1.9%_______4.0_______________10000______40000
__-1.4%_______8.0_______________10000______80000
__-0.9%______13.0_______________10000_____130000
__-0.4%______35.5_______________10000_____355000
___0.1%______13.0_______________40000_____520000
___0.6%_______8.0______________250000____2000000
___1.1%_______4.0______________562500____2250000
___1.6%_______3.0_____________2250000____6750000
___2.1%_______2.0_____________2250000____4500000
___2.6%_______2.0_____________2250000____4500000
___3.1%_______1.0_____________2250000____2250000
___3.6%_______0.5_____________2250000____1125000
Sum of Products = 24560000
Sq Root of Products = 4956
Times 1.1 = 5451 = Hourly standard deviation in $
[snip]
This is consistent with what I posted the other day about
computing variance from frequency distributions, so it
looks like I was probably right. -MH
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It's clear to see that we can derive other figures from the given info, such as advantage and win rate, and much more. The main factor is accuracy of the input, which will consequently result in corresponding accuracy in calculations.
ANS