Proving the Max Binomial Coefficient for n and r

In summary, the largest binomial coefficient C(n,r) where r is a nonnegative integer less than or equal to n is when r is either \lfloor{\frac{n}{2}\rfloor} or \lceil{\frac{n}{2}\rceil}. This can be proven by showing that in the even case, C(n,n/2) is larger than all other binomial coefficients for r < n and r not equal to n/2. This can be done by carefully using induction and showing that the coefficients for r from 0 to [n/2] are increasing.
  • #1
gimpy
28
0
Hi, I am having a little trouble with this proof:

Let n be a positive integer. What is the largest binomial coefficient [tex]C(n,r)[/tex] where r is a nonnegative integer less than or equal to n? Prove your answer is correct.

So let [tex]r = \lfloor{\frac{n}{2}\rfloor} [/tex] or [tex]r = \lceil{\frac{n}{2}\rceil} [/tex] then [tex]\left( \begin{array}{c} n \\ r \end{array} \right)[/tex] is the largest binomial coefficient.

Now I am having trouble with the proof. Where do i begin?
Maybe something like this?

[tex]\left( \begin{array}{c} n \\ \lfloor \frac{n}{2} \rfloor \end{array} \right) = \frac{n!}{\left(\lfloor \frac{n}{2} \rfloor \right)! \left(n - \lfloor \frac{n}{2} \rfloor \right)!} = ...[/tex]

Am i on the right track?
 
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  • #2
Yes you are on the right track. There are two cases depending on whether n is odd or even. Obviously the middle values are the biggest, just think of the Pascal triangle. Then I suppose you would prove that (in the even case) C(n,n/2) > C(n,r) for r < n and r not equal n/2. Consider writing n as 2m, so n/2 = m, and splitting out the facors: C(n,m) = n(n-1)...(m+1)/m(m-1)...1 compared to C(n,r) = n(n-1)...r/(n-r)(n-r-1)...1, and match factors.
 
  • #3
you can proceed as follows:

note that [tex]\binom{n}{r}=\binom{n}{n-r}[/tex] and that it thus suffices to show that the coeffs for r=0 to [n/2] (integral part) are increasing.

This follows from a *careful* induction argument (it's best to have two base cases going for n=2 and 3 say).
 

Related to Proving the Max Binomial Coefficient for n and r

1. What is the Max Binomial Coefficient for n and r?

The Max Binomial Coefficient for n and r refers to the largest possible value that can be obtained when calculating the binomial coefficient for a given value of n and r. It is also known as the "central binomial coefficient" and is denoted by the symbol C(n,r).

2. Why is proving the Max Binomial Coefficient important?

Proving the Max Binomial Coefficient is important because it allows us to determine the maximum possible number of combinations that can be formed from a given set of elements. It is a fundamental concept in combinatorics and has numerous applications in fields such as statistics, probability, and computer science.

3. How is the Max Binomial Coefficient calculated?

The Max Binomial Coefficient for n and r can be calculated using the formula C(n,r) = n! / (r!(n-r)!). This formula represents the number of ways to choose r elements from a set of n elements, without considering the order in which they are chosen. It can also be calculated using Pascal's Triangle, where the central element in each row represents the Max Binomial Coefficient for that row.

4. Can the Max Binomial Coefficient be proven using mathematical induction?

Yes, the Max Binomial Coefficient can be proven using mathematical induction. This involves proving the base case (when n = 0 or r = 0), and then using the induction hypothesis to prove the statement for n and r+1. By showing that the formula holds for all possible values of n and r, we can prove the Max Binomial Coefficient for any given combination.

5. Are there any real-life applications of the Max Binomial Coefficient?

Yes, the Max Binomial Coefficient has numerous real-life applications. It is used in probability and statistics to determine the number of possible outcomes in experiments or events. It is also used in computer algorithms for tasks such as generating all possible combinations or permutations of a given set of elements. Additionally, it has applications in fields such as genetics, economics, and social sciences.

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