Prob of red ball in buckets. Binomial?

In summary, the probability that a particular bucket will get $n$ red balls is:P(X=n)={R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}=1
  • #1
paolopiace
10
0
I know for many of you this sounds trivial. For me it's not...

A barrel contains M buckets each containing B balls, for a total of N = M x B balls.

N is a big number.

A small number R > 1 of balls are red. All the others N-R are white.

The location of each one of these R balls is random across the M buckets.
That means, one or more red balls can be in any bucket.

Now I randomly pull one bucket from the barrel.

What is the probability that X > 1 red balls are in that bucket?

Besides the final formula that I really need, may I also ask for a guidance to get to it?

Thank You!
 
Mathematics news on Phys.org
  • #2
I think we can ignore the white balls, and just imagine we have $M$ buckets before us, and $R$ red balls to randomly distribute among the buckets. Now, each time we put a red ball into a bucket, what is the probability that for any particular bucket, it will be the one that gets the ball?
 
  • #3
MarkFL said:
... what is the probability that for any particular bucket, it will be the one that gets the ball?

I think there are R/M probabilities to see one red ball in a particular bucket.
Then, there are (R-1)/M probabilities to see a second red ball in that same bucket.
Therefore R(R-1)/M^2 is the prob. to find two red balls in a particular bucket.

Kind of right? Or not?
 
  • #4
Each time we place a red ball into a bucket, the probability that a particular bucket will get the ball is:

\(\displaystyle P(X)=\frac{1}{M}\)

What is the probability that the bucket will not get the ball?
 
  • #5
MarkFL said:
... What is the probability that the bucket will not get the ball?

It's 1-1/M

I am kind of confused. If a throw R balls in the air, there are R/M probabilities that a specific bucket gets a ball. Or not?

1/M is the probability that a specific bucket gets a ball if I throw one and only one ball. Or nor?
 
Last edited:
  • #6
paolopiace said:
It's 1-1/M

I am kind of confused. If a throw R balls in the air, there are R/M probabilities that a specific bucket gets a ball. Or not?

Yes, that's right about a bucket not getting a ball. I am looking at this from the perspective that each placement of a red ball is a separate event. I find it simpler that way. :)

So using what we have found so far, what is the probability that a certain bucket will get $n$ red balls, where $0\le n\le R$?
 
  • #7
MarkFL said:
Yes, that's right about a bucket not getting a ball. I am looking at this from the perspective that each placement of a red ball is a separate event. I find it simpler that way. :)

So using what we have found so far, what is the probability that a certain bucket will get $n$ red balls, where $0\le n\le R$?

Let's look at a simple example...we have 3 red balls ($R=3$). Now suppose we want to compute the probability that a particular bucket gets 1 red ball. So, using what we have found, we would have:

\(\displaystyle \left(\frac{1}{M}\right)^1\left(\frac{M-1}{M}\right)^2\)

But...this is only the probability for one of the ways the bucket could get 1 red ball...it could get the red ball on the first distribution, or on the second, or on the third. So, the probability that a bucket will get 1 red ball is:

\(\displaystyle P(X=1)=3\left(\frac{1}{M}\right)^1\left(\frac{M-1}{M}\right)^2\)

Now, suppose we generalize back to $R$ red balls and $n$ red balls in a particular bucket. There will be $R$ distributions, and so we have $R$ "slots" to fill with either "Yes, got a ball" or "No, did not get a ball." Thus, we have $n$ yeses to distribute into $R$ slots.

For the first yes, we have $R$ choices, for the second we have $R-1$ choices and continuing all the way down to the $n$th yes, where we have $R-(n-1)$ choices. But, we must account for the fact that a yes going into a particular slot is equivalent to a yes going into that same slot on another choice. So, we must divide by the number of ways to arrange $n$ items, which is $n!$.

Putting all of this together, we find the number $N$ of distinct ways to distribute these yeses into the $R$ slots is given by:

\(\displaystyle N=\frac{R(R-1)(R-2)\cdots(R-(n-1))}{n!}=\frac{R!}{n!(R-n)!}={R \choose n}\)

What we have in fact just found is the number of ways to choose $n$ from $R$. :)

And so we find the probability that a particular bucket gets $n$ red balls is:

\(\displaystyle P(X=n)={R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}\)

Now, if this is correct, then we should find that the sum of the probabilities for $n=0$ to $n=R$ is 1, since it is certain that any bucket will get some number of red balls from $0$ to $R$:

\(\displaystyle \sum_{n=0}^R\left({R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}\right)=1\)

We should recognize that the LHS of the above equation is an application of the binomial theorem, and so we may write:

\(\displaystyle \left(\frac{1}{M}+\frac{M-1}{M}\right)^R=1\)

\(\displaystyle \left(\frac{M-1+1}{M}\right)^R=1\)

\(\displaystyle \left(\frac{M}{M}\right)^R=1\)

\(\displaystyle (1)^R=1\)

\(\displaystyle 1=1\)

So, our formula checks out and we have in essence derived the binomial probability formula. Can you now use this formula to answer the given question:

\(\displaystyle P(X>1)=?\)
 
  • #8
Just to finish this up, we have:

\(\displaystyle \sum_{n=0}^R\left({R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}\right)=1\)

And we can write this as:

\(\displaystyle {R \choose 0}\left(\frac{1}{M}\right)^0\left(\frac{M-1}{M}\right)^{R-0}+{R \choose 1}\left(\frac{1}{M}\right)^1\left(\frac{M-1}{M}\right)^{R-1}+\sum_{n=2}^R\left({R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}\right)=1\)

Now, we should recognize that:

\(\displaystyle P(X>1)=\sum_{n=2}^R\left({R \choose n}\left(\frac{1}{M}\right)^n\left(\frac{M-1}{M}\right)^{R-n}\right)\)

And so, making that substitution, and simplifying, we obtain:

\(\displaystyle \left(\frac{M-1}{M}\right)^{R}+R\left(\frac{1}{M}\right)\left(\frac{M-1}{M}\right)^{R-1}+P(X>1)=1\)

Solving for $P(X>1)$, we find:

\(\displaystyle P(X>1)=1-\left(\frac{M-1}{M}\right)^{R}-\frac{R}{M}\left(\frac{M-1}{M}\right)^{R-1}\)
 
  • #9
MarkFL said:
Just to finish this up, we have: ...

This is beautiful!
I want to thank you so much, although I still have to digest it entirely.
Sorry for this late feedback. Many things of life kept me away from my post.
 

Related to Prob of red ball in buckets. Binomial?

1. What is the binomial distribution?

The binomial distribution is a probability distribution that describes the likelihood of obtaining a certain number of successes in a fixed number of independent trials with two possible outcomes, such as success or failure.

2. How is the binomial distribution related to the probability of a red ball in buckets?

The binomial distribution can be used to calculate the probability of obtaining a certain number of red balls in a fixed number of trials, assuming the probability of success (i.e. getting a red ball) remains constant for each trial.

3. What is the formula for calculating the probability of a red ball in buckets using the binomial distribution?

The formula is P(x) = nCx * p^x * (1-p)^(n-x), where n is the number of trials, x is the number of successes, and p is the probability of success.

4. What is the difference between the binomial distribution and the probability of a red ball in buckets?

The binomial distribution is a mathematical model used to calculate the probability of a certain number of successes in a fixed number of trials, while the probability of a red ball in buckets refers to the actual likelihood of obtaining a red ball in a given set of buckets.

5. How can the binomial distribution be applied in real-life situations?

The binomial distribution can be applied in various fields, such as genetics, finance, and manufacturing, to predict the likelihood of a certain number of successes or failures in a specific number of trials. For example, it can be used to determine the probability of a certain number of defective products in a batch of manufactured goods.

Similar threads

Replies
11
Views
4K
  • General Math
Replies
2
Views
819
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
723
  • General Math
Replies
14
Views
3K
Replies
2
Views
2K
Replies
1
Views
629
Replies
8
Views
2K
Replies
6
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
Replies
11
Views
2K
Back
Top