Binomial Distribution satisfies Marcoff Chain

In summary, the Binomial Distribution in the form P_{N}(m)=\frac{N!}{(\frac{N+m}{2})!(\frac{N-m}{2})!}p^{\frac{N+m}{2}}q^{\frac{N-m}{2}}satisfies the marcoff chain P_{N+1}\left(m\right)=pP_{N}\left(m-1\right)+qP_{N}\left(m+1\right) by factoring out the N! and manipulating the denominators to match the denominator in P_{N+1}(m).
  • #1
ppedro
22
0
1. The problem statement

Consider the Binomial Distribution in the form

[itex]P_{N}(m)=\frac{N!}{(\frac{N+m}{2})!(\frac{N-m}{2})!}p^{\frac{N+m}{2}}q^{\frac{N-m}{2}}[/itex]

where [itex]p+q=1[/itex], [itex]m[/itex] is the independent variable and [itex]N[/itex] is a parameter.

Show that it satisfies the marcoff chain

[itex]P_{N+1}\left(m\right)=pP_{N}\left(m-1\right)+qP_{N}\left(m+1\right)[/itex]

2. The attempt at a solution

I'm trying my solution starting from this:

[itex]pP_{N}\left(m-1\right)+qP_{N}\left(m+1\right)[/itex]


[itex]=p\frac{N!}{\left(\frac{N+m-1}{2}\right)!\left(\frac{N-m+1}{2}\right)!}p^{\frac{N+m-1}{2}}q^{\frac{N-m+1}{2}}+q\frac{N!}{\left(\frac{N+m+1}{2}\right)!\left(\frac{N-m-1}{2}\right)!}p^{\frac{N+m+1}{2}}q^{\frac{N-m-1}{2}}[/itex]


[itex]=\frac{N!}{\left(\frac{N+m-1}{2}\right)!\left(\frac{N-m+1}{2}\right)!}p^{\frac{N+m+1}{2}}q^{\frac{N-m+1}{2}}+\frac{N!}{\left(\frac{N+m+1}{2}\right)!\left(\frac{N-m-1}{2}\right)!}p^{\frac{N+m+1}{2}}q^{\frac{N-m+1}{2}}[/itex]


[itex]=p^{\frac{N+m+1}{2}}q^{\frac{N-m+1}{2}}\left(\frac{N!}{\left(\frac{N+m-1}{2}\right)!\left(\frac{N-m+1}{2}\right)!}+\frac{N!}{\left(\frac{N+m+1}{2}\right)!\left(\frac{N-m-1}{2}\right)!}\right)[/itex]


I can't go any further. If you can help I would appreciate.
 
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  • #2
(Edit) See what happens if you multiply by##\frac{N+1}{N+1}##.
 
  • #3
My previous comment was based on a particular way that I went about it which got to the result. But, on review, I see that multiplying by (N+1)/(N+1) isn't necessary.

I would factor out the ##N!## in your expression.

The important thing is to get the two denominators in your expression to match the denominator in ##P_{N+1}(m)##. For example, what could you multiply the numerator and denominator of ##\frac{1}{\left(\frac{N+m-1}{2}\right)!\left(\frac{N-m+1}{2}\right)!}## by to get the denominator in ##P_{N+1}(m)##?

[By the way, welcome to PF, ppedro!]
 
  • #4
Hey TSny! Thanks for your reply. I see what you're suggesting but I'm not being able to compute it. The factorials are not helping me simplify the expression.
 
  • #5
##P_{N+1}(m)## has a denominator of ##(\frac{N+m+1}{2})!(\frac{N-m+1}{2})!##.

Compare that to your first denominator ##(\frac{N+m-1}{2})!(\frac{N-m+1}{2})!##.

To get your denominator to match the denominator in ##P_{N+1}(m)##, you've got to somehow transform ##(\frac{N+m-1}{2})!## into ##(\frac{N+m+1}{2})!##.

What can you multiply ##(\frac{N+m-1}{2})!## by to produce ##(\frac{N+m+1}{2})!##?
 
  • #6
[itex]\frac{(N+m+1)!}{(N+m-1)!}=\frac{(N+m+1)(N+m)(N+m-1)!}{(N+m-1)!}=(N+m+1)(N+m)
[/itex]
 
  • #7
No. Note that ##\frac{N+m+1}{2} = \frac{N+m-1}{2} + 1##.
 
  • #8
Ok, I see your point. Thanks!
 

Related to Binomial Distribution satisfies Marcoff Chain

1. What is the Binomial Distribution?

The Binomial Distribution is a probability distribution that describes the probability of obtaining a certain number of successes in a set number of independent trials, where the probability of success remains constant for each trial.

2. How does the Binomial Distribution satisfy the Marcoff Chain?

The Marcoff Chain is a mathematical concept that describes the probability of transitioning from one state to another. The Binomial Distribution satisfies the Marcoff Chain because it models the probability of transitioning from one outcome (success or failure) to another in a series of independent trials.

3. Can the Binomial Distribution be used for continuous data?

No, the Binomial Distribution is only applicable for discrete data, where the number of trials is finite and the probability of success remains constant.

4. What is the relationship between the Binomial Distribution and the Normal Distribution?

The Binomial Distribution can be approximated by the Normal Distribution when the number of trials is large and the probability of success is not extremely small or extremely large. This is known as the Central Limit Theorem.

5. How is the Binomial Distribution used in real-world applications?

The Binomial Distribution is commonly used in fields such as statistics, finance, and biology to model the probability of success or failure in a given scenario. It can be used to predict the likelihood of outcomes and make informed decisions based on the data.

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