Conditional probability - Random number of dice

In summary: Now, since the sum of all N outcomes for even N is 1/2, and we know that the sum of all S outcomes for N=2 is 1/2, we can say that:In summary, the probability of S = 4 given that N is even is equal to the sum of the probabilities of N = 2 and S = 4, divided by the sum of all even N outcomes, which is 1/2. This can be calculated by first finding the probabilities of N = 2 and S = 4, and then multiplying by 2. For part b, the probability that the largest number shown by any die is r, where the sum of the scores is unknown, can be
  • #1
Alexsandro
51
0
Can someone help me with this question ?

A random number N of dice is thrown. Let Ai be the event that N = i, and assume that P(Ai) = 1/(2)^i, i >= 1. The sum of the scores is S. Find the probability that:

(a) S = 4, given N is even;
(b) the largest number shown by any die is r, where S is unknown.
 
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  • #2
(a) [tex]P(S=4 \text{ and N is even})/P(\text{N is even})=[/tex]
[tex]P\left(\left\{N=2 \text{ and }(S=1+3 \text{ or }S=2+2 \text{ or }S=3+1)\right\}\text{ OR }\{N=4\text{ and }S=1+1+1+1\}\right)\left/ \sum_{k=1}^\infty 2^{-2k}\right.[/tex]

If the world is just, then the denominator should add up to 1/2. Because P(odd) = P(even) and P(odd) + P(even) = 1, so P(odd) = P(even) = 1/2.

So calculating P(S=4 and N is even)/P(N is even) is a matter of calculating the numerator and then multiplying it with 2.
 
  • #3
For part b:

The chance that [itex]r[/itex] is the largest value shown is going to be
[tex]\sum_{i=1}^{\infty} P(A_i) \times p(r,i)[/tex]
where
[tex]p(r,i)[/itex]
is the probability that [itex]r[/itex] is the largest value shown by [itex]i[/itex] dice.

Now, the chance of all of the dice being less than or equal to [itex]r[/itex], assuming that [itex]r\in{1,2,3,4,5,6}[/itex] is going to be
[tex]\left(\frac{r}{6}\right)^{i}[/itex]
and of those
[tex]\left(\frac{r-1}{6}\right)^{i}[/itex]
don't contain any [itex]r[/itex]
So we have
[tex]\sum_{i=1}^{\infty} \frac{r^i-(r-1)^i}{12^i}=\sum_{i=1}^{\infty}\left(\frac{r}{12}\right)^i - \sum_{i=1}^{\infty}\left(\frac{r-1}{12}\right)^i=\frac{r}{12-r}-\frac{r-1}{13-r}=\frac{13r-r^2-12r+r^2+12-r}{156-25r+r^2}=\frac{12}{r^2-25r+156}[/tex]
So
[tex]r=6 \rightarrow \frac{12}{156+36-150}= \frac{12}{42} = \frac{2}{7}[/tex]
[tex]r=5 \rightarrow \frac{12}{156+25-125}= \frac{12}{56} = \frac{3}{14}[/tex]
[tex]r=4 \rightarrow \frac{12}{156+16-100}= \frac{12}{72} = \frac{1}{6}[/tex]
[tex]r=3 \rightarrow \frac{12}{156+9-75}=\frac{12}{90}= \frac{2}{15}[/tex]
[tex]r=2 \rightarrow \frac{12}{156+4-50}=\frac{12}{110}=\frac{6}{55}[/tex]
[tex]r=1 \rightarrow \frac{12}{156+1-25}=\frac{12}{132}=\frac{1}{11}[/tex]
 
  • #4
The question of the part (a) is P(S = 4 | N is even) and not P(S = 4 and N is even | N is even).
 
  • #5
Alexsandro said:
The question of the part (a) is P(S = 4 | N is even) and not P(S = 4 and N is even | N is even).
That's what EnumaElish did. By the definition of conditional probability:

[tex]P(A|C)=\frac{P(A \cap C)}{P(C)}[/tex]

Which is, by the way, trivially equal to [itex]P(A\cap C|C)[/itex].
 

1. What is conditional probability?

Conditional probability is the probability of an event occurring given that another event has already occurred or is assumed to have occurred. It is denoted by P(A|B) where A and B are events.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the joint occurrence of two events by the probability of the given event. In the case of random number of dice, it would be the probability of getting a certain number on the second dice, given that a certain number was already rolled on the first dice.

3. What is the difference between conditional probability and unconditional probability?

Unconditional probability is the probability of an event occurring without any other conditions or events taken into consideration. On the other hand, conditional probability takes into account a previous event or condition and calculates the probability of another event occurring.

4. Can conditional probability be used in real-life situations?

Yes, conditional probability is used in various fields such as finance, medicine, and weather forecasting. For example, in finance, conditional probability can be used to calculate the probability of a stock market crash given certain economic conditions.

5. How is the concept of conditional probability related to random number of dice?

In the case of random number of dice, conditional probability can be used to calculate the probability of getting a certain number on the second dice, given that a certain number was already rolled on the first dice. It is also used to calculate the probability of obtaining a certain combination of numbers on multiple dice rolls.

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