Balls in a box shaking experiment

In summary, the conversation discusses the probability of a specific ball configuration occurring in a box containing V balls, where Ng are green, Nr are red, and Nb are blue. The probability is defined as the frequency of occurrence when the box is repeatedly shaken and observed. The specific probability in question is P(G, R) which represents the probability of G green balls and R red balls being on the left half of the box, under the assumption that G+R is less than half of V. The probability is calculated using the formula Gamma(G,R)/Gamma(total), where Gamma(G,R) is equal to the number of ways to select and arrange the desired balls on the left half of the box, and Gamma(total) is equal to the total
  • #1
rmjmu507
36
0
A box contains V balls of which N[itex]_{g}[/itex] are green, N[itex]_{r}[/itex] are red and V-N[itex]_{g}[/itex]-N[itex]_{r}[/itex]=N[itex]_{b}[/itex] are blue.
Now somebody shakes the box vigorously, brings it to rest and then observes the
arrangement of the balls in the box. Suppose this is repeated many times so that
probabilities of different ball configurations can be defined as frequencies of occurrence.

What is the probability, P(G, R) that there are G green balls and R red balls in the
left half of the box? (Assume G+R<V/2)

I believe this probability is equal to [itex]\Gamma[/itex](G, R)/[itex]\Gamma[/itex](total)...

In this case, I think [itex]\Gamma[/itex](G, R) would be:

[itex]\Gamma[/itex](G, R) = (([itex]\frac{(N_g)!}{(N_g)!(V-N_r-N_b)!}[/itex][itex])^2)((\frac{(N_r)!}{(N_r)!(V-N_g-N_b)!}[/itex])^2)(([itex]\frac{V}{2}[/itex]!)^2)

And [itex]\Gamma[/itex](total) is V!.

Does this look right? In the first expression, the first term represents the number of ways to select which green balls are on the left hand side times the number of ways to select which red balls are on the left hand side, the second term represents the number of ways to select which red balls are on the left hand side times the number of ways to select which green balls are on the left hand side, and the third term represents the number of ways to arrange V/2 balls on the LHS times the number of ways to arrange V/2 balls on the RHS.

Am I on the right track?
 
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  • #2
You need to clarify. Do you assume that each ball is equally likely to end up on the left or the right half of the box, and that the final positions of the balls are independent (which might NOT be a reasonable assumption since if part of the box gets too crowded, it may force balls into the other part!)?
 
  • #3
every arrangement of the balls is equally likely to occur. in other words, every arrangement will occur with equal frequency.

and yes, independence is assumed. the balls are identical except for their color
 
  • #4
rmjmu507 said:
A box contains V balls of which N[itex]_{g}[/itex] are green, N[itex]_{r}[/itex] are red and V-N[itex]_{g}[/itex]-N[itex]_{r}[/itex]=N[itex]_{b}[/itex] are blue.
Now somebody shakes the box vigorously, brings it to rest and then observes the
arrangement of the balls in the box. Suppose this is repeated many times so that
probabilities of different ball configurations can be defined as frequencies of occurrence.

What is the probability, P(G, R) that there are G green balls and R red balls in the
left half of the box? (Assume G+R<V/2)

I believe this probability is equal to [itex]\Gamma[/itex](G, R)/[itex]\Gamma[/itex](total)...

In this case, I think [itex]\Gamma[/itex](G, R) would be:

[itex]\Gamma[/itex](G, R) = (([itex]\frac{(N_g)!}{(N_g)!(V-N_r-N_b)!}[/itex][itex])^2)((\frac{(N_r)!}{(N_r)!(V-N_g-N_b)!}[/itex])^2)(([itex]\frac{V}{2}[/itex]!)^2)

And [itex]\Gamma[/itex](total) is V!.

Does this look right? In the first expression, the first term represents the number of ways to select which green balls are on the left hand side times the number of ways to select which red balls are on the left hand side, the second term represents the number of ways to select which red balls are on the left hand side times the number of ways to select which green balls are on the left hand side, and the third term represents the number of ways to arrange V/2 balls on the LHS times the number of ways to arrange V/2 balls on the RHS.

Am I on the right track?
None of your below-the-line terms look right. What happened to G and R?
I'd expect to see terms like (Ng C G), etc.
 
  • #5


Yes, you are on the right track. Your calculation for \Gamma(G, R) is correct. The first two terms represent the number of ways to select G green balls and R red balls from a total of N_{g} and N_{r} balls respectively, while the last term represents the number of ways to arrange these balls on the left half of the box. The total number of arrangements is represented by \Gamma(total) which is V!. Therefore, the probability of having G green balls and R red balls in the left half of the box is \Gamma(G, R)/\Gamma(total). This approach is valid assuming the balls are randomly distributed within the box after each shake.
 

FAQ: Balls in a box shaking experiment

What is the purpose of a balls in a box shaking experiment?

The purpose of a balls in a box shaking experiment is to study the behavior of a system under controlled conditions. This type of experiment can help scientists better understand how particles move and interact with each other.

How does a balls in a box shaking experiment work?

In a balls in a box shaking experiment, a number of small balls are placed inside a closed box. The box is then shaken at a specific frequency and amplitude, causing the balls to collide with each other and the walls of the box. The movements of the balls can be recorded and analyzed to study the behavior of the system.

What factors can affect the outcome of a balls in a box shaking experiment?

The outcome of a balls in a box shaking experiment can be affected by various factors such as the size and number of balls, the shape and size of the box, the frequency and amplitude of shaking, and the type of material the balls and box are made of.

What can be learned from a balls in a box shaking experiment?

A balls in a box shaking experiment can provide insights into the properties and behavior of a system, such as the pressure, temperature, and energy distribution. It can also help scientists understand how particles interact and how these interactions can affect the overall behavior of the system.

What are some real-world applications of balls in a box shaking experiments?

Balls in a box shaking experiments have various real-world applications, such as understanding the behavior of gases, studying the properties of materials, and developing new technologies like particle accelerators and fluidized bed reactors. They can also be used in industries such as pharmaceuticals, food processing, and materials science to optimize processes and improve product quality.

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