OK, Basic Statistical Binomial probability evaluations:
n= number of times an experiment is repeated (for us 200)
F= What will count as a successfull experiment (for us "success" is a misfire)
n= How many times we need/want a success to occur (for us 1)
n! F(x)= x!(n-x)! * (F
x)(x
(n-x))
So how this works, when we say 1 out 200 times, that means that EACH time you fire your musket there is a chance that that shot will misfire equal to that that one guy will have a misfire when 200 men shoot all at the same time.
This next parrt is where people are getting confused:
Each experiment (Shot taken) is independant. Meaning that the success or failure of one trial(attempt) does not affect the outcome of the next trial(Shot taken/attempt). [
There is a way of making the probability cummulative, (Each failure makes success a little more likely) however we would not want that in this scenario.]
So saying that the chance that 1 of 200 shots will misfire, is actually a failry rare. you may only experience a misfire once every few battles even. So I do not belive this to be a bad idea.
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If there are misfires, it needs to be COMPLETLY random. They should actually ask some historians to estimate the chances of a misfire are and put that into the game. If it is something like every 20 shots than people can count and fire there 20th shot into the air and than reload again.
Also, we are not saying an incrimental value. (i.e every 20
th shot will misfire.) The purpose of stateting that 1 of 200 accounts that the outcomes are placed at equally likely with each trial yielding a random occurance.
I think it should be around 1 in 50 personally. A line of 50 men all fire, 1 of them has a misfire.
I see where you are going with that, however Binomial Probability Distribution does not work EXACTLY that way, but you have the right idea. And I may even agree that 1 of 200 is a little to rare. But I would say no more than 1 of 150 (Mabe as low as 1 of 100...maybe)
(Please Pardon any misspellings and such, I only had 10 min to type this on a break at work)