Binomial Coefficient Factorial Derivation

In summary, the conversation discusses the concept of binomial coefficients and how to construct them using Pascal's recursion and induction. The conversation also delves into the relationship between binomial coefficients and Pascal's triangle, and how to define them in terms of arranging objects of different colors. The conversation also mentions various stories and resources related to the topic. Finally, it ends with a brief discussion on the total number of permutations of an arrangement and how it relates to the number of permutations satisfying a certain condition.
  • #1
Odious Suspect
43
0
A few decades ago my algebra teacher showed how to construct the expression for binomial coefficients. If I start with Pascal's recursion, and propose C(n,k)=n!/k!(n-k)!, I can prove it to be so through induction. But that doesn't give me that happy feeling that comes with understanding.

It can't be that hard; so I'm feeling really dumb at this point. How does one build up the relationship C(n,k)=n!/k!(n-k)! from scratch?
 
Mathematics news on Phys.org
  • #2
Is your ##C(n,k)## the number in Pascal's triangle at position ##(n,k)## or the number of combinations of ##k## balls out of ##n##?
I know it's the same. I ask for definition.
 
  • #3
If you have ##n## things and ##k## of them are one colour (white, say) and the remaining ##n-k## of them are another colour (black), then there are ##\frac{n!}{k!(n-k)!}## ways to arrange them.

To see this, imagine they are numbered ##1 - n##. The total number of ways of arranging them is ##n!##. But, how many are the same black/white pattern - ignoring the numbers and looking just at the colour?

First, the ##k## white things can be put in any order - that's ##k!## - without changing the white/black pattern. And, the ##n-k## black things can likewise be re-arranged in any order without changing the pattern.

The total number of white/black patterns is, therefore, ##\frac{n!}{k!(n-k)!}##

Now, think of the ##n## objects (all black, say), numbered and in order. We want to pick any ##k##. This is what ##\binom{n}{k}## means: how many ways to choose ##k## objects from ##n##.

If we do this by marking the ones we choose as white, then we see that every choice corresponds to a black/white pattern and vice versa. And, therefore, we have:

##\binom{n}{k} = \frac{n!}{k!(n-k)!}##
 
  • #4
I'm still not sure whether I understood you. Say you have n numbered balls which k of them are black and white the rest. There are n! ways to order them. If you now decide to just look at the colors you have to divide by the k! orderings of black balls and (n-k)! orderings of white balls.
There are plenty of stories about this triangle. Some are here: http://www.mathsisfun.com/pascals-triangle.html
Ok, the page looks a bit childish. Nevertheless it might give you a kind of intuition.
 
  • #5
i[tex]B=\left\{b_1,b_2,\ldots ,b_n\right\},\text{Null}b_i=T|F[/tex]

[tex]B_j=\left\{b_{j_1},b_{j_2},\ldots ,b_{j_n}\right\}[/tex] is the ##j^{\text{th}}## permutation of ##B##, so ##B_0=B##.

##A\left(B_j\right)## is an arrangement of ##B## such that [itex]A\left(B_j\right)=A\left(B_k\right)[/itex] means [itex]\left\{b_{j_1},b_{j_2},\ldots ,b_{j_n}\right\}=\left\{b_{k_1},b_{k_2},\ldots ,b_{k_n}\right\}[/itex]. That is to say, [itex]T=b_{j_i}=b_{k_i}[/itex] or [itex]F=b_{j_i}=b_{k_i}[/itex]

[tex]B=C[B,k]\Rightarrow b_1=b_2=,\ldots ,=b_k=T\land b_{k+1}=b_{k+2}=,\ldots ,=b_n=F[/tex]

[itex]P(B,j)=B_j[/itex] is the transformation from [itex]B[/itex] to [itex]B_j[/itex]

Let [itex]A_q=A(P(B,q))=A\left(B_q\right)[/itex] where [itex]q[/itex] is the smallest permutation index for permutations with the same arrangement.

The number of arrangements [itex]A_q[/itex] for a given [itex]C[B,k][/itex] is [itex]\left(\begin{array}{c} n \\ k \\ \end{array} \right)[/itex].

If [itex]A(B)=A\left(B_m\right)[/itex] then [itex]A(P(B,j))=A\left(P\left(B_m,j\right)\right)[/itex]

To find the number of arrangements we divide the total number of permutation by the number of permutations satisfying [itex]A\left(B_j\right)=A_0[/itex]

The total number of permutations of [itex]B[/itex] is [itex]n![/itex]. The number of permutations satisfying [itex]A(C[B,k])[/itex] is the number of permutations of [itex]\left\{b_1,b_2,\ldots ,b_k\right\}[/itex] times the number of permutations of [itex]\left\{b_{k+1},b_{k+2},\ldots ,b_n\right\}[/itex]. That is [itex]k! (n-k)![/itex].

Unfortunately, the library is closing, so this is fire and forget. I don't have time to proof it.
 
Last edited by a moderator:
  • #6
I have to admit, I cheated. This gave me the nudge that got me started.
 

1. What is a binomial coefficient?

A binomial coefficient represents the number of ways to choose a set of objects from a larger set, without regard to order. It is written as "n choose k" and is denoted as nCk or n choose k. It is calculated using the formula nCk = n! / (k! * (n-k)!).

2. What is the factorial of a number?

The factorial of a number is the product of all positive integers less than or equal to that number. It is represented by the symbol ! and is calculated using the formula n! = n * (n-1) * (n-2) * ... * 1.

3. How is the binomial coefficient calculated?

The binomial coefficient is calculated using the formula nCk = n! / (k! * (n-k)!). This formula represents the number of combinations of size k that can be chosen from a set of n objects.

4. What is the connection between binomial coefficients and factorials?

The binomial coefficient is calculated using the factorial function because it represents the number of ways to choose a subset of objects from a larger set. The factorial function is used to calculate the total number of possible arrangements of the objects, and then the formula nCk = n! / (k! * (n-k)!) is used to determine the number of combinations of those arrangements.

5. How is binomial coefficient factorial derivation used in mathematics?

Binomial coefficient factorial derivation is used in various fields of mathematics, including combinatorics, probability, and statistics. It is used to calculate the number of possible outcomes in different situations, such as in the binomial theorem, in the expansion of polynomials, and in the calculation of probabilities in experiments with two outcomes.

Similar threads

Replies
15
Views
1K
  • Linear and Abstract Algebra
Replies
2
Views
999
Replies
4
Views
365
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
Replies
5
Views
1K
  • Precalculus Mathematics Homework Help
Replies
15
Views
2K
  • Calculus and Beyond Homework Help
Replies
5
Views
1K
  • General Math
Replies
3
Views
4K
Back
Top