How Does the Distribution of Heads in Coin Flipping Change with Large N?

In summary, the distribution of different numbers of heads and tails when flipping N fair coins should be peaked at N/2 and the peak will be very high when N is large. An expression for this distribution near the peak can be found using Stirling's approximation and ln(1+x)=x for small x. However, extra corrections need to be taken into account when expanding to the 2nd order, resulting in an expression of -2x^2 /N rather than 4x^2 /N. The width of the peak increases as sqrt(N), but considering the ratio of heads to coins, the width decreases as 1/sqrt(N).
  • #1
chingcx
21
0

Homework Statement



Flip N fair coins. The distribution for different numbers of heads and tails should be peaked at N/2. When N is very large, the peak will be very high. Let x = N(head)-N/2, required to find an expression for this distribution near the peak, i.e. x<<N.

Homework Equations



Strling Approx
ln(1+x)=x for small x

The Attempt at a Solution



30bjvyr.jpg


clearly incorrect because square of (N/2)! must be smaller than the product of (N/2+x)! and (N/2-x)!, but I can't find where goes wrong.
 
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  • #2
1. Going over to the 5th line, you omitted [itex]-x \ln{(\frac{N}{2}+x)}[/itex] and [itex]x \ln{(\frac{N}{2}-x)}[/itex]. These give rise to additional corrections.
[itex]-x \ln{(\frac{N}{2}+x)}+x\ln{(\frac{N}{2}-x)}=-x\ln{\left(\frac{1+2x/N}{1-2x/N}\right)}\approx -x\ln{(1+4x/N)}\approx -4x^2 /N[/itex]

2. In the 7th line, you need to be more careful when expanding to the 2nd order. You should proceed as below.
[itex]\ln \left(\frac{N/2}{N/2+x}\right) = \ln \left(\frac{1}{1+2x/N}\right) \approx \ln \left( 1-\frac{2x}{N}+\frac{4x^2}{N^2} \right) \approx -\frac{2x}{N}+\frac{4x^2}{N^2}-\frac{1}{2} {\left(-\frac{2x}{N}+\frac{4x^2}{N^2} \right)}^{2} [/itex]

[itex] \approx -\frac{2x}{N}+\frac{4x^2}{N^2}-\frac{1}{2} \frac{4x^2}{N^2} = -\frac{2x}{N}+\frac{2x^2}{N^2}[/itex]

and similarly

[itex]\ln \left(\frac{N/2}{N/2-x}\right) \approx \frac{2x}{N}+\frac{2x^2}{N^2} [/itex]


Then, the final answer becomes [itex]-2x^2 /N[/itex] rather than [itex]4x^2 /N [/itex].
 
  • #3
weejee said:
1. Going over to the 5th line, you omitted [itex]-x \ln{(\frac{N}{2}+x)}[/itex] and [itex]x \ln{(\frac{N}{2}-x)}[/itex]. These give rise to additional corrections.
[itex]-x \ln{(\frac{N}{2}+x)}+x\ln{(\frac{N}{2}-x)}=-x\ln{\left(\frac{1+2x/N}{1-2x/N}\right)}\approx -x\ln{(1+4x/N)}\approx -4x^2 /N[/itex]

2. In the 7th line, you need to be more careful when expanding to the 2nd order. You should proceed as below.
[itex]\ln \left(\frac{N/2}{N/2+x}\right) = \ln \left(\frac{1}{1+2x/N}\right) \approx \ln \left( 1-\frac{2x}{N}+\frac{4x^2}{N^2} \right) \approx -\frac{2x}{N}+\frac{4x^2}{N^2}-\frac{1}{2} {\left(-\frac{2x}{N}+\frac{4x^2}{N^2} \right)}^{2} [/itex]

[itex] \approx -\frac{2x}{N}+\frac{4x^2}{N^2}-\frac{1}{2} \frac{4x^2}{N^2} = -\frac{2x}{N}+\frac{2x^2}{N^2}[/itex]

and similarly

[itex]\ln \left(\frac{N/2}{N/2-x}\right) \approx \frac{2x}{N}+\frac{2x^2}{N^2} [/itex]


Then, the final answer becomes [itex]-2x^2 /N[/itex] rather than [itex]4x^2 /N [/itex].
Thanks, but it doesn't make sense... when N is very large, the peak should be very narrow, but from the equation, N becomes larger then the exponential decreases much slower.
 
  • #4
You are right. The width of the peak actually increases, as sqrt(N).
Yet, if you consider (# of heads)/(# of coins), the width decreases as 1/sqrt(N).
 

FAQ: How Does the Distribution of Heads in Coin Flipping Change with Large N?

What is statistical physics?

Statistical physics is a branch of physics that studies the behavior of systems made up of a large number of particles. It uses statistical methods to analyze and predict the macroscopic properties of these systems based on the microscopic interactions between particles.

What are the main concepts in statistical physics?

The main concepts in statistical physics include entropy, probability distributions, and the Boltzmann distribution. Entropy is a measure of the disorder or randomness in a system, while probability distributions describe the likelihood of different states of a system. The Boltzmann distribution relates the energy of a system to the probability of being in a particular state.

How is statistical physics used in real-world applications?

Statistical physics has many practical applications, including in materials science, thermodynamics, and even finance. It can be used to understand and predict the behavior of materials such as metals and polymers, as well as the flow of heat and energy in complex systems. In finance, statistical physics principles can be applied to understand and model the behavior of markets and economies.

What is the difference between classical and quantum statistical physics?

Classical statistical physics deals with systems of particles that are large enough to be described using classical mechanics. Quantum statistical physics, on the other hand, takes into account the quantum nature of particles and their interactions. It is used to study systems at the atomic and subatomic level.

What are some key principles of statistical physics?

Some key principles of statistical physics include the law of large numbers, which states that the average behavior of a large number of particles becomes more predictable and deterministic; the principle of microstate equilibration, which states that systems tend to evolve towards their most probable state over time; and the principle of detailed balance, which describes the equilibrium between different states of a system. Other important principles include the ergodic hypothesis, which assumes that time averages and ensemble averages are equal, and the equipartition theorem, which relates the energy of a system to its temperature.

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