C(n,n/2)/(2^(N+1)) > 1/(2*sqrt(n))

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In summary, the conversation discusses a homework problem involving an inequality for even numbers and the use of Stirling's formula to obtain upper and lower bounds. The original inequality is shown to be false and the conversation moves on to discussing a different statement from a book.
  • #1
neginf
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Homework Statement



For n even, C(n,n/2)/(2^(N+1)) > 1/(2*sqrt(n)).

Homework Equations



sqrt(2*pi*k) * k^k * e^-k < k! < sqrt(2*pi*k) * k^k * e^-k * (1 + 1/4*k)

The Attempt at a Solution



Have tried using the inequality to get lower bound for C(n,n/2), but get something smaller than 1/(2*sqrt(n)).
 
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  • #2
neginf said:

Homework Statement



For n even, C(n,n/2)/(2^(N+1)) > 1/(2*sqrt(n)).

Homework Equations



sqrt(2*pi*k) * k^k * e^-k < k! < sqrt(2*pi*k) * k^k * e^-k * (1 + 1/4*k)

The Attempt at a Solution



Have tried using the inequality to get lower bound for C(n,n/2), but get something smaller than 1/(2*sqrt(n)).

If your inequality is *exactly* as written, it is false. Look at R(n) = 2*sqrt(n)*C(n,n/2)/2^(n+1). We can easily plot it, and see that it is strictly increasing, starting at R(1) = 1/sqrt(pi) = 0.6366 and rising asymptotically to R(infinity) = sqrt(2/pi) = 0.7979. In other words, we never have R(n) > 1, which your inequality gives. We can get simple bounds on R(n) by using bounds S(k) < k! < S(k)*exp(1/ 12k) [see Feller, Intro. to Probability for a simple proof], where S(k) = sqrt(2*pi*k)*k^k*exp(-k) is Stirling's formula. Then we get a lower bound on R(n) by using the lower bound in the numerator and upper bounds in the denominator, and vice-versa for an upper bound. In this way we get:
sqrt(2/pi)*exp(-1/ 3n) < R(n) < sqrt(2/pi)*exp(1/ 12n). The upper bound is < 1 for all n >= 1.

RGV
 
  • #3
Sorry for the mistake. This is from the top of page 17 in Approximation Of Functions By Rivlin,
unless I'm reading it wrong. If you're familiar with the book, I'd be grateful for some help with this.
 
  • #4
neginf said:
Sorry for the mistake. This is from the top of page 17 in Approximation Of Functions By Rivlin,
unless I'm reading it wrong. If you're familiar with the book, I'd be grateful for some help with this.

I don't have the book, and since retiring and moving away from my old university I no longer have access to its books---only to some e-journals. What, exactly, is the statement you want to prove?

RGV
 

FAQ: C(n,n/2)/(2^(N+1)) > 1/(2*sqrt(n))

What does the equation "C(n,n/2)/(2^(N+1)) > 1/(2*sqrt(n))" represent?

The equation represents a mathematical inequality that is commonly used in probability and combinatorics to analyze the relationship between combinations and permutations. It compares the value of the combination C(n,n/2) to the value of 1/(2*sqrt(n)) multiplied by a factor of 2^(N+1).

How is this equation related to the concept of probability?

The equation is related to the concept of probability through the use of combinations, which are used to calculate the number of possible outcomes in a given scenario. The inequality allows us to determine the likelihood of a particular event occurring based on the number of possible outcomes.

What is the significance of the value "n" in the equation?

The value "n" represents the total number of elements or objects in a given set. It is a crucial factor in determining the value of the combination C(n,n/2) and plays a role in analyzing the probability of a particular event occurring.

How does the value "N" affect the inequality?

The value "N" represents the number of trials or experiments that are being conducted. It is used to adjust the inequality to account for multiple trials and allows us to analyze the probability of a particular event occurring over a series of trials.

Can this inequality be used to solve real-world problems?

Yes, this inequality can be used to solve real-world problems involving probability and combinations. It can be applied in various fields such as genetics, economics, and computer science to analyze and predict the likelihood of certain outcomes based on the given parameters.

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