Extension on a simple probability question

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SUMMARY

The discussion centers on calculating probabilities in experiments involving dice rolls, specifically transitioning from two dice to seven dice. The probability of rolling a sum of 7 with two dice is established as 6/36. For more complex scenarios, such as finding the probability of seven dice summing to 15, participants suggest using discrete random variables and probability mass functions (pmf). Techniques like discrete convolutions and counting methods (combinations and permutations) are recommended for solving these advanced probability problems.

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  • Knowledge of probability mass functions (pmf)
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  • Learn about discrete convolutions in probability theory
  • Study the computation of probability mass functions (pmf)
  • Explore combinatorial techniques for counting sample points
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trap101
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An experiment consists of tossing a pair of dice:

1) Determine the number of sample points in the sample space

2) Find the probability that the sum of the numbers appearing on the dice is equal to 7


Issue: Ok so I know how to do this problem, but my question comes with respect to the second portion. In this specific problem I am able to count the different sample points that make the dice add up to 7 i.e: 6/36 is the answer, but what if this was a larger problem? e.g: Say that instead of 2 dice I had 7 dice and I needed to find the probability of the seven dice adding up to 15...What technique would I have to use to find/count all those sample points? It surely can't be by counting each one individually?
 
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There are always many different techniques to solve probability problems. For example, I could define a discrete random variable S as the sum of 7 i.i.d. uniform random variables X~U[1,6]. Then, I could compute the probability mass function of S with 7 discrete convolutions, with the answer being F_S(15) where F_S is the pmf of S.

You can also use counting methods (combinations, permutations, etc.).
 
RoshanBBQ said:
There are always many different techniques to solve probability problems. For example, I could define a discrete random variable S as the sum of 7 i.i.d. uniform random variables X~U[1,6]. Then, I could compute the probability mass function of S with 7 discrete convolutions, with the answer being F_S(15) where F_S is the pmf of S.

You can also use counting methods (combinations, permutations, etc.).





Ahhh. You see I haven't reached that part of my text yet. I looked through it but haven't done any of the work involving those concepts, but now I see what your getting at. Thanks
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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