Pigeonhole Principle and the Arithmetic Mean

In summary, the pigeonhole principle states that if m objects are distributed into k containers where m > k, then one container must have more than the floor of (m-1)/k objects. As a corollary, it is obvious that the arithmetic mean of a set of numbers is between its smallest and largest values. This can be seen by interpreting the mean as the number of objects in each container when distributing the numbers into k containers, and then using the pigeonhole principle to show that each container must have at least the smallest number of objects.
  • #1
Dschumanji
153
1
My discrete mathematics book gives the following definition for the pigeonhole principle:

If m objects are distributed into k containers where m > k, then one container must have more than [itex]\lfloor[/itex][itex]\frac{m-1}{k}[/itex][itex]\rfloor[/itex] objects.

It then states as a corollary that the arithmetic mean of a set of numbers must be in between the smallest and largest numbers of the set. No proof is given, it pretty much just says "well it's just obvious that this is the case."

I think it is obvious that the arithmetic mean of a set of numbers is in between its smallest and largest values. What isn't obvious to me is how their definition of the pigeonhole principle leads to the corollary. Can anyone help me out?
 
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  • #2
Hmmm... well I can interpret it so that the arithmetic mean is larger than the smallest number:

Taking the mean of numbers n1,...,nk is the same thing as having k containers with ni objects in the ith container, and then re-distributing them so that each container has an even amount. (the number of objects in each container is the mean) WLOG suppose that n1 is the smallest number (otherwise just re-arrange). There must be at least n1*k objects, and hence by the pigeonhole principle, one container (and hence all of them) must have more than the floor of (n1k-1)/k = n1-1objects. Hence they have at least n1 objects each.

There are missing details in the case that the mean is not exactly an integer, but then the containers each hold a number of objects that is smaller than the mean so it still works.
 

1. What is the Pigeonhole Principle?

The Pigeonhole Principle is a mathematical concept that states that if there are more objects than there are categories to put them in, then at least one category must contain more than one object.

2. How is the Pigeonhole Principle related to the Arithmetic Mean?

The Pigeonhole Principle can be used to prove the existence of an Arithmetic Mean for a set of numbers. This means that if a set of numbers has more elements than the largest number in the set, then there must be a number in the set that is equal to or greater than the Arithmetic Mean.

3. Can the Pigeonhole Principle be used in other areas of mathematics?

Yes, the Pigeonhole Principle has applications in many areas of mathematics, including combinatorics, number theory, and probability. It is a useful tool for proving the existence of certain mathematical objects.

4. How is the Pigeonhole Principle used in computer science?

The Pigeonhole Principle can be used in computer science to analyze algorithms and data structures. It can help determine the minimum amount of space or time required for a certain task, or to prove the existence of a solution to a problem.

5. What is an example of the Pigeonhole Principle in real life?

An example of the Pigeonhole Principle in real life is the fact that in a room of 367 people, at least two people must have the same birthday. This is because there are only 366 possible birthdays (excluding February 29th) and there are more people in the room than there are possible birthdays.

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