Conditional probability - Random number of dice

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The discussion focuses on calculating conditional probabilities involving a random number of dice thrown, specifically addressing two parts. For part (a), the probability of the sum S equaling 4 given that N is even is explored, emphasizing the need to calculate the numerator and multiply by 2 for the final result. Part (b) examines the probability that the largest number shown by any die is r, with a detailed formula provided for calculating this probability based on the number of dice and their outcomes. The calculations involve summing probabilities for different values of r and applying the concept of conditional probability correctly. The thread highlights the importance of understanding the definitions and relationships between events in probability theory.
Alexsandro
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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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(a) P(S=4 \text{ and N is even})/P(\text{N is even})=
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.

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.
 
For part b:

The chance that r is the largest value shown is going to be
\sum_{i=1}^{\infty} P(A_i) \times p(r,i)
where
p(r,i)[/itex]<br /> is the probability that r is the largest value shown by i dice.<br /> <br /> Now, the chance of all of the dice being less than or equal to r, assuming that r\in{1,2,3,4,5,6} is going to be<br /> \left(\frac{r}{6}\right)^{i}[/itex]&lt;br /&gt; and of those&lt;br /&gt; \left(\frac{r-1}{6}\right)^{i}[/itex]&amp;lt;br /&amp;gt; don&amp;amp;#039;t contain any r&amp;lt;br /&amp;gt; So we have&amp;lt;br /&amp;gt; \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}&amp;lt;br /&amp;gt; So&amp;lt;br /&amp;gt; r=6 \rightarrow \frac{12}{156+36-150}= \frac{12}{42} = \frac{2}{7}&amp;lt;br /&amp;gt; r=5 \rightarrow \frac{12}{156+25-125}= \frac{12}{56} = \frac{3}{14}&amp;lt;br /&amp;gt; r=4 \rightarrow \frac{12}{156+16-100}= \frac{12}{72} = \frac{1}{6}&amp;lt;br /&amp;gt; r=3 \rightarrow \frac{12}{156+9-75}=\frac{12}{90}= \frac{2}{15}&amp;lt;br /&amp;gt; r=2 \rightarrow \frac{12}{156+4-50}=\frac{12}{110}=\frac{6}{55}&amp;lt;br /&amp;gt; r=1 \rightarrow \frac{12}{156+1-25}=\frac{12}{132}=\frac{1}{11}
 
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).
 
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:

P(A|C)=\frac{P(A \cap C)}{P(C)}

Which is, by the way, trivially equal to P(A\cap C|C).
 
The book claims the answer is that all the magnitudes are the same because "the gravitational force on the penguin is the same". I'm having trouble understanding this. I thought the buoyant force was equal to the weight of the fluid displaced. Weight depends on mass which depends on density. Therefore, due to the differing densities the buoyant force will be different in each case? Is this incorrect?

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