The probabililty of 3 rolls of dice and get two 6's

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The discussion revolves around calculating the probability of rolling two 6's in three dice rolls. Various methods were attempted, including straightforward multiplication and binomial equations, but initial calculations yielded incorrect results. The correct approach involves using the binomial distribution, specifically the formula for the probability of getting exactly two successes (rolling a 6) in three trials. The final consensus suggests using the binomial coefficient combined with the probabilities of rolling a 6 and not rolling a 6 to arrive at the correct answer. Understanding the proper application of these formulas is essential for accurate probability calculations.
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I was asked to help someone to work out the probability above. It was more than a year since I done similar questions and thing do get rusty... So I hope to work it out here and get point out where I did wrong before I show that person the correct answer.

Intuitively there is three ways I came up to solve the problem, which apparently gave different answers. So it's either one or two or all three methods are wrong. Methods I came to mind are:

1) 1/6 * 1/6 * 5/6 = 0.023 -> this is the first idea came to my mind, since there is only 3trials and the probability of getting a 6 is 1/6, so I use the multiply rule to times things together. The results seems rather small, so I doubt this is the correct method.

2) 3C2 * 1/6 * (5/6)^2 = 0.347 -> I got this by using the binomial equation

3) 3C2 * 1/6 * 5/6 = 0.416 -> I got this by using the Bernoulli equation i.e. n*p*q. where n is the number of all possible outcomes, p is the probability of getting a 6, and q is the probability of not getting a 6.

Please check which methods I used was correct, and if neither of them was correct please suggest a way to work this out.
 
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Hi Philip!

The first one is wrong because you just consider the case [6, 6, x], you need to consider also the cases [6, x, 6] and [x, 6, 6], that is 3 \cdot 0.023.. \sim 0.069

The second case is wrong because you raised to the power of two the wrong probability
{3\choose 2} \cdot (1/6)^2 \cdot 5/6 \sim 0.069 which also explains why you also got wrong the Bernoulli formula.

Good luck getting "unrusted"! :wink:
 
usually this is solved by considering the converse probability: what's the probability of not getting any 6's in three rolls and then use the 100% - P to get the probability that you want.
 
Philip Wong said:
I was asked to help someone to work out the probability above. It was more than a year since I done similar questions and thing do get rusty... So I hope to work it out here and get point out where I did wrong before I show that person the correct answer.

Intuitively there is three ways I came up to solve the problem, which apparently gave different answers. So it's either one or two or all three methods are wrong. Methods I came to mind are:

1) 1/6 * 1/6 * 5/6 = 0.023 -> this is the first idea came to my mind, since there is only 3trials and the probability of getting a 6 is 1/6, so I use the multiply rule to times things together. The results seems rather small, so I doubt this is the correct method.

2) 3C2 * 1/6 * (5/6)^2 = 0.347 -> I got this by using the binomial equation

3) 3C2 * 1/6 * 5/6 = 0.416 -> I got this by using the Bernoulli equation i.e. n*p*q. where n is the number of all possible outcomes, p is the probability of getting a 6, and q is the probability of not getting a 6.

Please check which methods I used was correct, and if neither of them was correct please suggest a way to work this out.

Hey Philip Wong.

The best way I think to do this is to use a binomial distribution with 3 trials where one state corresponds to rolling a 6 and the other not rolling a 6. Each dice roll is independent (assumed) and has the same probabilities. In this case p = 1/6 and 1-p = 5/6

This means your probability is given 3C2 p^2 x (1-p) = 3C2 x 5/192 = 15/192

You can visualize this by drawing a tree diagram of the events on paper. Use two events: a 6 for one and a non-6 for everything else and then you will get a tree with 8 possibilities with three levels of depth.
 
chiro said:
Hey Philip Wong.

The best way I think to do this is to use a binomial distribution with 3 trials where one state corresponds to rolling a 6 and the other not rolling a 6. Each dice roll is independent (assumed) and has the same probabilities. In this case p = 1/6 and 1-p = 5/6

This means your probability is given 3C2 p^2 x (1-p) = 3C2 x 5/192 = 15/192

You can visualize this by drawing a tree diagram of the events on paper. Use two events: a 6 for one and a non-6 for everything else and then you will get a tree with 8 possibilities with three levels of depth.

viraltux said:
Hi Philip!

The first one is wrong because you just consider the case [6, 6, x], you need to consider also the cases [6, x, 6] and [x, 6, 6], that is 3 \cdot 0.023.. \sim 0.069

The second case is wrong because you raised to the power of two the wrong probability
{3\choose 2} \cdot (1/6)^2 \cdot 5/6 \sim 0.069 which also explains why you also got wrong the Bernoulli formula.

Good luck getting "unrusted"! :wink:

Hi guys,
Thanks for your help. So what I should do if I were to keep using the Bernoulli formula (n.p.q) what I should really do is:
{3\choose 2} \cdot (1/6)^2 \cdot 5/6

I knew I had either misplaced or missed something in the formula.
So if I used what I've provided before, i.e. {3\choose 2} \cdot (1/6) \cdot (5/6)^2 what it really meant was, the probability of only getting one 6 out of the three dice roll right?

thanks
 
Philip Wong said:
So if I used what I've provided before, i.e. {3\choose 2} \cdot (1/6) \cdot (5/6)^2 what it really meant was, the probability of only getting one 6 out of the three dice roll right?

thanks

Nope, it would be the probability of getting anything but 6 in both dices.
 
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