What is the Combinatorial Interpretation of this Sum?

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Discussion Overview

The discussion centers around finding a combinatorial interpretation of the sum \sum_{k=0}^{n}\binom{k}{r}\binom{n-k}{m-r}. Participants explore various interpretations and transformations of the sum, considering its implications in combinatorial contexts.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants inquire about the combinatorial interpretation of the given sum, noting that a similar sum over r would yield n C m.
  • One participant suggests that the sum equals (n+1) C (m+1) after experimenting with specific values.
  • Another participant proposes a literal translation of the sum, describing it as counting the ways to choose elements from specified ranges based on k.
  • There is a discussion about the differences in interpretations of sets of elements and the role of the integer k in the selection process.
  • One participant suggests a transformation that relates the original sum to a set of m+1 elements in {1, ..., n+1}, involving adjustments to the chosen elements based on k.
  • Another participant introduces a visualization using balls in boxes to clarify the combinatorial interpretation.
  • A later reply connects the identity to Laplace's Rule of Succession, discussing its implications in probability without taking limits.

Areas of Agreement / Disagreement

Participants express differing views on the interpretation of the sum and its transformations. While some interpretations are proposed, there is no consensus on a definitive combinatorial meaning or resolution of the various interpretations discussed.

Contextual Notes

The discussion involves multiple interpretations and transformations of the sum, with participants exploring various combinatorial contexts and implications. Some assumptions and dependencies on definitions remain unresolved.

Who May Find This Useful

This discussion may be of interest to those studying combinatorial mathematics, probability theory, or related fields, particularly in understanding the nuances of combinatorial identities and their interpretations.

techmologist
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Is there a combinatorial interpretation of the sum

\sum_{k=0}^{n}\binom{k}{r}\binom{n-k}{m-r} ?

If it were a sum over r instead, it would be n C m. But I don't know about this one.
 
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After plugging in a few numbers and playing around with it, I found that the sum is, surprisingly, equal to (n+1) C (m+1). Maybe knowing this will make it easier to come up with an interpretation.
 
Well, there is a sort of literal translation: it's counting the number of ways to:

  • Pick an integer k
  • Choose r elements from {1, ..., k}
  • Choose m-r elements from {1, ..., n-k}

Well, it's easy to reorganize the data:

  • Pick an integer k
  • Choose r elements from {1, ..., k}
  • Choose m-r elements from {k+1, ..., n}

and

  • Choose m elements from {1, ..., n}
  • Pick an integer such that r of the elements are less than or equal to k
 
Hurkyl said:
Well, there is a sort of literal translation: it's counting the number of ways to:

  • Pick an integer k
  • Choose r elements from {1, ..., k}
  • Choose m-r elements from {1, ..., n-k}

Well, it's easy to reorganize the data:

  • Pick an integer k
  • Choose r elements from {1, ..., k}
  • Choose m-r elements from {k+1, ..., n}
...

Ah, I see where you are going with that. But isn't that going to come out to n C m?
 
Actually, I wasn't going anywhere -- those were just simplifications I saw off the top of my head. I stopped once I noticed a path to start following in earnest!

Do you not see the difference between:
  • A set of m elements in {1, ..., n} along with an integer k such that r of the chosen elements are less than or equal to k,
  • A set of m elements in {1, ..., n}?

Anyways, the path forward I saw was to look for a way to insert an extra object into the setup to represent k.
 
Hurkyl said:
Actually, I wasn't going anywhere -- those were just simplifications I saw off the top of my head. I stopped once I noticed a path to start following in earnest!

Do you not see the difference between:
  • A set of m elements in {1, ..., n} along with an integer k such that r of the chosen elements are less than or equal to k,
  • A set of m elements in {1, ..., n}?

Well, yes, but if k is an element of {1,...,n}, then aren't you choosing from n elements? And if it is not in {1, ..., n}, then all m elements are less than k.

Anyways, the path forward I saw was to look for a way to insert an extra object into the setup to represent k.

Okay. Maybe I misunderstood what you were saying before. Are we adding an extra object to n ordered objects that are labeled {1,...,n} in such a way that it is still distinguishable from another object (an integer, presumably) of the same value? Or are we actually dealing with the integers 1,...,n themselves? That's what I assumed at first. Thank you.
 
The final transformation is to realize
A set of m elements in {1, ..., n} along with an integer k such that r of the chosen elements are less than or equal to k​
contains the same data as
A set of m+1 elements in {1, ..., n+1}/indent]

To convert from the second to the first, let k be the r+1-th number (in sorted order). Remove k from the original list, and subtract one from k and from every chosen number bigger than k.

To convert from the first to the second, add one to every chosen number greater than k, then add k+1 to the list of chosen numbers.


Maybe balls in boxes will make it more clear. From the data
A set of m elements in {1, ..., n} along with an integer k such that r of the chosen elements are less than or equal to k​
we can depict it by lining up n boxes and placing m white balls into the boxes. Then insert one extra box between k and k+1 with a red ball.​
 
Thank you, Hurkyl, for taking the time to explain it in detail. That makes sense now.

EDIT:

BTW, the above identity allows one to prove Laplace's celebrated (and abused) Rule of Succession without having to take limits.

An urn contains n balls. The number k of red balls is determined randomly so that the possibilities k = 0, 1, ..., n, are equally likely. The remaining n-k balls are white. You do not know the fraction of red balls. You draw m balls, r of which are red. What is the probability that the (m+1)st is red? Conditional on k, the probability that r of the first m, as well as the (m+1)st balls are red is

\frac{\binom{k}{r}\binom{n-k}{m-r}}{\binom{n}{m}}\frac{k-r}{n-m} = \frac{r+1}{m+1}\frac{\binom{k}{r+1}\binom{n-k}{(m+1)-(r+1)}}{\binom{n}{m+1}}

Summing over k gives

\frac{r+1}{m+1}\frac{\binom{n+1}{m+2}}{\binom{n}{m+1}}

which is proportional to the unconditional probability that r of the first m as well as the (m+1)st balls are red. The constant of proportionality is P(k) = 1/(n+1). Similarly, the unconditional probability that r of the first m balls are red is proportional to

\frac{\binom{n+1}{m+1}}{\binom{n}{m}} by the same constant P(k) = 1/(n+1).

Finally, divide the first by the second and apply Bayes' theorem to get

P{\text{(m+1)st ball is red} | \text{r of the first m were red}} = \frac{(r+1)\binom{n}{m}\binom{n+1}{m+2}}{(m+1)\binom{n+1}{m+1}\binom{n}{m+1}} = \frac{r+1}{m+2}

So, of course, if you flip a coin once and it comes up heads, that means it comes up heads on the next flip with probability 2/3! :biggrin:
 
Last edited:

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