Occupancy Problem (Wackerly & Mendenhall & Schaeffer Problem 2.93)

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  • Thread starter Ackbach
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In summary: Your reasoning is correct. The numerical answers also agree with mine, so I believe it is correct. Well done!In summary, we are given five bowls with different numbers of white and black balls and we are asked to find the probability of selecting two white balls when randomly selecting a bowl and then two balls from that bowl without replacement. We find that the probability of selecting two white balls is 2/5 and the probability that bowl 3 was selected given that two white balls were selected is 3/20.
  • #1
Ackbach
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Problem 2.93. Five identical bowls are labeled $1, 2, 3, 4,$ and $5$. Bowl $i$ contains $i$ white and $5-i$ black balls, with $i=1, 2, \dots, 5$. A bowl is randomly selected and two balls are randomly selected (without replacement) from the contents of the bowl.
  • What is the probability that both balls selected are white?
  • Given that both balls selected are white, what is the probability that bowl $3$ was selected?

Answer. Let $B_i$ be the event that bowl $i$ is selected. Let $W_1$ be the event that the first ball taken is white, and let $W_2$ be the event that the second ball taken is white. We are given the following data:
$$P(B_i)=1/5;\quad P(W_1|B_i)=i/5;\quad P(W_2|B_i\cap W_1)=(i-1)/4; \quad P(W_2|B_i\cap \overline{W_1})=i/4.$$
  • We are asked to compute $P(W_2|W_1)$. If $W_1$ has occurred, then the probability of getting a second white ball from bowl $i$ is $(i-1)/4$. So, we find $P(W_2|W_1)$ as follows:
    \begin{align*}
    P(W_2|W_1)&=\sum_{i=1}^{5}P(B_i\cap W_1) \, P(W_2|B_i\cap W_1) \\
    &=\sum_{i=1}^{5}P(B_i) \, P(W_1|B_i) \, P(W_2|B_i\cap W_1) \\
    &=\sum_{i=1}^{5}\left(\frac15 \right) \left(\frac{i}{5} \right)\left(\frac{i-1}{4}\right) \\
    &=\frac{1}{100}\sum_{i=1}^{5}(i^2-i) \\
    &=\frac{1}{100}\left(\frac{5(6)(11)}{6}-15\right) \\
    &=\frac25.
    \end{align*}
  • We are asked to compute $P(B_3|W_1\cap W_2)$. Note that
    $$P(W_1\cap W_2)\, P(B_3|W_1\cap W_2)=P(B_3) \, P(W_1\cap W_2|B_3) $$
    $$\implies P(B_3|W_1\cap W_2)=\frac{P(B_3) \, P(W_1\cap W_2|B_3)}{P(W_1\cap W_2)}
    =\frac{P(B_3) \, P(W_1\cap W_2|B_3)}{P(W_1) \, P(W_2|W_1)}.$$
    To assemble the ingredients of this formula, we note immediately that
    \begin{align*}
    P(B_3)&=\frac15 \\
    P(W_1\cap W_2|B_3)&=\frac35 \cdot \frac24 =\frac35 \cdot \frac12 = \frac{3}{10} \\
    P(W_2|W_1)&=\frac25 \\
    P(W_1)&=\sum_{i=1}^{5}P(B_i) \, P(W_1|B_i)=\frac15 \sum_{i=1}^{5}\frac{i}{5}=
    \frac{15}{25}=\frac35.
    \end{align*}
    It follows, then, that
    $$P(B_3|W_1\cap W_2)=\frac{\frac15 \cdot \frac{3}{10}}{\frac35 \cdot \frac25}
    =\frac{3}{50} \cdot \frac{25}{6}=\frac{1}{2}\cdot \frac{1}{2}=\frac{1}{4}.$$

The first part a is, I am fairly sure, correct. However, I think part b is incorrect. What am I doing wrong? Thank you for your time!
 
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  • #2
Ackbach said:
Problem 2.93. Five identical bowls are labeled $1, 2, 3, 4,$ and $5$. Bowl $i$ contains $i$ white and $5-i$ black balls, with $i=1, 2, \dots, 5$. A bowl is randomly selected and two balls are randomly selected (without replacement) from the contents of the bowl.
  • What is the probability that both balls selected are white?
  • Given that both balls selected are white, what is the probability that bowl $3$ was selected?

Answer. Let $B_i$ be the event that bowl $i$ is selected. Let $W_1$ be the event that the first ball taken is white, and let $W_2$ be the event that the second ball taken is white. We are given the following data:
$$P(B_i)=1/5;\quad P(W_1|B_i)=i/5;\quad P(W_2|B_i\cap W_1)=(i-1)/4; \quad P(W_2|B_i\cap \overline{W_1})=i/4.$$
  • We are asked to compute $P(W_2|W_1)$. If $W_1$ has occurred, then the probability of getting a second white ball from bowl $i$ is $(i-1)/4$. So, we find $P(W_2|W_1)$ as follows:
    \begin{align*}
    P(W_2|W_1)&=\sum_{i=1}^{5}P(B_i\cap W_1) \, P(W_2|B_i\cap W_1) \\
    &=\sum_{i=1}^{5}P(B_i) \, P(W_1|B_i) \, P(W_2|B_i\cap W_1) \\
    &=\sum_{i=1}^{5}\left(\frac15 \right) \left(\frac{i}{5} \right)\left(\frac{i-1}{4}\right) \\
    &=\frac{1}{100}\sum_{i=1}^{5}(i^2-i) \\
    &=\frac{1}{100}\left(\frac{5(6)(11)}{6}-15\right) \\
    &=\frac25.
    \end{align*}
  • We are asked to compute $P(B_3|W_1\cap W_2)$. Note that
    $$P(W_1\cap W_2)\, P(B_3|W_1\cap W_2)=P(B_3) \, P(W_1\cap W_2|B_3) $$
    $$\implies P(B_3|W_1\cap W_2)=\frac{P(B_3) \, P(W_1\cap W_2|B_3)}{P(W_1\cap W_2)}
    =\frac{P(B_3) \, P(W_1\cap W_2|B_3)}{P(W_1) \, P(W_2|W_1)}.$$
    To assemble the ingredients of this formula, we note immediately that
    \begin{align*}
    P(B_3)&=\frac15 \\
    P(W_1\cap W_2|B_3)&=\frac35 \cdot \frac24 =\frac35 \cdot \frac12 = \frac{3}{10} \\
    P(W_2|W_1)&=\frac25 \\
    P(W_1)&=\sum_{i=1}^{5}P(B_i) \, P(W_1|B_i)=\frac15 \sum_{i=1}^{5}\frac{i}{5}=
    \frac{15}{25}=\frac35.
    \end{align*}
    It follows, then, that
    $$P(B_3|W_1\cap W_2)=\frac{\frac15 \cdot \frac{3}{10}}{\frac35 \cdot \frac25}
    =\frac{3}{50} \cdot \frac{25}{6}=\frac{1}{2}\cdot \frac{1}{2}=\frac{1}{4}.$$

The first part a is, I am fairly sure, correct. However, I think part b is incorrect. What am I doing wrong? Thank you for your time!

Shouldn't the numerator be $P(B_{3}{\cap}W_{1}{\cap}W_{2})=\frac{1}{5}.\frac{3}{5}.\frac{1}{2}=\frac{3}{50}$? EDIT: sorry, that's what you've got. Why do you think the answer's wrong?
 
  • #3
I've found your problem. In a) you should be finding $P(W_{1}{\cap}W_{2})$, not $P(W_{2}|W_{1})$. Then for b) you get $\frac{3}{50}.\frac{5}{2}=\frac{3}{20}$
 
  • #4
Ok, so let's do this:

  • We are asked to compute $P(W_1\cap W_2)$. Now the entire sample space
    $\displaystyle S=\bigcup_{i=1}^{5}B_i$, with $B_i\cap B_j=\varnothing$ whenever $i\not=j$. That is, the $B_{i}$ partition $S$. It follows from the Law of Total Probability that
    $$P(W_1\cap W_2)=\sum_{i=1}^{5}P(B_i) \, P(W_1\cap W_2|B_i).$$
    Now
    $$P(W_1\cap W_2|B_i)=\frac{i}{5} \cdot \frac{i-1}{4}=\frac{i^2-i}{20}.$$
    Hence,
    $$P(W_1\cap W_2)=\frac{1}{100}\sum_{i=1}^{5}(i^2-i)=\frac{2}{5}.$$
  • Then, following your lead, we have
    $$P(B_3|W_1\cap W_2)=\frac{P(B_3) \, P(W_1\cap W_2|B_3)}{P(W_1\cap W_2)}
    =\frac{(1/5)(3/5)(2/4)}{2/5}=\frac{3}{20}.$$

Is this reasoning correct? The numerical answers agree with the back of the book, and it certainly seems correct to me.
 
  • #5
Ackbach said:
Ok, so let's do this:

  • Is this reasoning correct? The numerical answers agree with the back of the book, and it certainly seems correct to me.


  • Yes.
 

FAQ: Occupancy Problem (Wackerly & Mendenhall & Schaeffer Problem 2.93)

What is the Occupancy Problem (Wackerly & Mendenhall & Schaeffer Problem 2.93)?

The Occupancy Problem, also known as the Wackerly & Mendenhall & Schaeffer Problem 2.93, is a mathematical problem that involves calculating the probability of at least one collision among a group of n randomly selected objects placed into m boxes. It is commonly used in statistics and probability courses to demonstrate concepts such as independence and the binomial distribution.

How is the Occupancy Problem calculated?

The Occupancy Problem is typically calculated using the formula P(at least one collision) = 1 - P(no collisions) = 1 - (m/m)^n. This formula assumes that the objects are randomly distributed among the boxes and that the number of objects is less than or equal to the number of boxes.

What is the significance of the Occupancy Problem?

The Occupancy Problem has applications in various fields, including statistics, computer science, and physics. It helps to demonstrate the concept of independence and the binomial distribution, which are fundamental concepts in these fields. It is also used to solve real-world problems, such as estimating the likelihood of collisions in computer networks or estimating the number of defective items in a sample.

What are the limitations of the Occupancy Problem?

The Occupancy Problem assumes that the objects are randomly distributed among the boxes, which may not always be the case in real-world scenarios. It also assumes that the number of objects is less than or equal to the number of boxes, which may not be true in some cases. Additionally, the problem does not account for any factors that may affect the likelihood of collisions, such as the size or shape of the objects.

How is the Occupancy Problem related to other mathematical problems?

The Occupancy Problem is closely related to other mathematical problems, such as the Birthday Problem and the Coupon Collector's Problem. These problems all involve calculating the probability of at least one collision or match among a group of randomly selected objects in different scenarios. They are also all used to demonstrate important concepts in probability and statistics.

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