SidYuca said:
...I propose to put each of 2 nines in 2 Green (for good) Balls...
I'm afraid that your strategy of trying to compensate for the different powers of three in 3 and 6 vs. 9 by adjusting the number of green balls in your model is not a valid way to calculate the probabilities. It leads to a rather big discrepancy between the odds calculated by your model and the actual odds of not getting a multiple of nine when repeatedly multiplying together randomly selected single digit numbers.
Fortunately, it doesn't appear to be particularly difficult to calculate the odd directly, without resorting to your black ball/green ball model. According to my calculations, the odds of not getting a multiple of nine when multiplying together n numbers randomly selected from {2,3,4,5,6,7,8,9} are given by the formula
(5/8)^(n-1) * (2*n+5)/8
In particular, for the case n=8 that you are considering, the odds are
(5/8)^7 * 21/8 = 9.78% (approximately)
By way of comparison, the odds predicted by your model of getting eight straight black balls when choosing from a mixture of 10 black balls and four green balls are
(10/14)^8 = 6.78% (approximately)
So, if my calculations are correct, your model is off by exactly 3% from the true odds, when the numbers are rounded to two decimal places.
I think kwbMitel is right in predicting that the large variability in the number of single digit multipliers needed to produce a seven digit product will make it impossible to calculate the odds without resorting to a lengthy enumeration of cases that will need to be carried out by computer. Just calculating the odds for each n and then performing some sort of average is bound to be too inaccurate to improve on the Monte Carlo-style simulations that several people in this thread have already performed. Their results strongly suggest that the odds of getting a seven digit number that's divisible by nine are within a percent or so of 94%