Probability Generating Functions Question

In summary: I'm sorry. I was reading carelessly: I didn't see the words "six independent trials" at first.The probability of rolling an 18 on one roll is 1/216.For the probability of rolling ≥ 2 in 6 trials, we can use the Binomial Probability Formula:P(Rolling 18 ≥ 2 in 6 trials) = 1 - P(0 18s) - P(1 18) = 1 - (215/216)6 - (6)(1/216)(215/216)5 ≈ .00031755 To calculate the expected number of repeats before getting ≥ 2 18s, we can use the Geometric Distribution with p
  • #1
Tim 1234
11
0

Homework Statement


In playing a certain game, your ability scores are determined by six independent rolls of three dice. After each set of six rolls, you are given the choice of keeping your scores or starting over.

(a) How many times should you expect to start over in order to get a set of ability scores with at least two scores that are 18?

Homework Equations


Binomial Probability Formula = (N choose K)Pkqn-k

E(X)=1/p
From the PGF for Geometric Distribution

The Attempt at a Solution



Probability of rolling three sixes (18) is 1/216.

P(Rolling 18 ≥ 2 in 6 trials) = 1 - P(0 18s) - P(1 18)
= 1 - (215/216)6 - (6)(1/216)(215/216)5 ≈ .00031755
(Binomial Probability Formula)

Using the Geometric (.00031755) Distribution, E(X) = 1/p = 1/.00031755 ≈ 3149

Where E(X) is the expected number of repeats before getting ≥ 2 18s.

[/B]
 
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  • #2
Tim 1234 said:

Homework Statement


In playing a certain game, your ability scores are determined by six independent rolls of three dice. After each set of six rolls, you are given the choice of keeping your scores or starting over.

(a) How many times should you expect to start over in order to get a set of ability scores with at least two scores that are 18?

Homework Equations


Binomial Probability Formula = (N choose K)Pkqn-k

E(X)=1/p
From the PGF for Geometric Distribution

The Attempt at a Solution



Probability of rolling three sixes (18) is 1/216.

P(Rolling 18 ≥ 2 in 6 trials) = 1 - P(0 18s) - P(1 18)
= 1 - (215/216)6 - (6)(1/216)(215/216)5 ≈ .00031755
(Binomial Probability Formula)

Using the Geometric (.00031755) Distribution, E(X) = 1/p = 1/.00031755 ≈ 3149

Where E(X) is the expected number of repeats before getting ≥ 2 18s.
[/B]

Please clarify: (1) If you decide to start over, do you discard your current scores and go back to 0? (It sound like you do.) (2) If on one roll of 6 dice you get a total of 36 , does that automatically count as two '18s'? (3) Are we allowed to make six rolls (of 6 dice in each roll), getting 6 each time, for a total of 36 = 18 ×2? (4) What has any of this to do with probability generating functions?
 
  • #3
If you start over, all of your current scores are discarded.

The trials consist of 6 independent rolls of three dice. So, you have a set of 6 sums of the roll of three dice.
So to get two "18s" you would need to roll three sixes twice in 6 attempts at rolling three dice.
 
  • #4
Tim 1234 said:
If you start over, all of your current scores are discarded.

The trials consist of 6 independent rolls of three dice. So, you have a set of 6 sums of the roll of three dice.
So to get two "18s" you would need to roll three sixes twice in 6 attempts at rolling three dice.

Of course: you did say that, more or less.
 

1. What is a probability generating function?

A probability generating function (PGF) is a mathematical function that describes the probability distribution of a discrete random variable. It is used to calculate the probabilities of different outcomes of a random experiment.

2. How is a probability generating function different from a probability mass function?

A probability mass function (PMF) gives the probability of each possible outcome of a discrete random variable, while a probability generating function gives the probabilities of all possible outcomes at once.

3. What is the purpose of a probability generating function in probability theory?

PGFs are used to simplify calculations in probability theory, as they provide a way to find the probabilities of multiple outcomes at once. They are also used to derive other important properties of discrete random variables, such as moments and cumulative distribution functions.

4. Can a probability generating function be used for continuous random variables?

No, probability generating functions are only applicable to discrete random variables. For continuous random variables, a similar concept called a moment generating function is used.

5. How do you calculate the probability generating function for a given random variable?

The probability generating function for a discrete random variable can be calculated by taking the sum of all possible outcomes multiplied by their respective probabilities. It can also be written as a power series, where each term represents the probability of a different outcome raised to a certain power.

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