Maximizing b(n,k) in Bernoulli Trials Homework

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In summary, we can determine the value of k for which b(n,k) is maximal by finding the value of j such that b(n,j) is maximal. Using the relations b(n,j-1) < b(n,j) and b(n,j+1) < b(n,j), we can simplify the ratio r(j) = b(n,j+1)/b(n,j) to determine that j < p(n+1) < j+1. The final solution is j \leq p(n+1) \leq j+1.
  • #1
jgens
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Homework Statement



Suppose [itex]0 < p < 1[/itex]. Define [itex]b(n,k) = \binom{n}{k}p^k(1-p)^k[/itex]. For what value of [itex]k[/itex] is [itex]b(n,k)[/itex] a maximum?

Homework Equations



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The Attempt at a Solution



Is there any way to get a nice closed form solution to this problem? I've already proved that it has a maximum so there must be some j such that [itex]b(n,j)[/itex] is maximal. Then we know [itex]b(n,j+1) < b(n,j)[/itex] and [itex]b(n,j-1) < b(n,j)[/itex]. And I figure we can use these relations to figure out j or something like that. But I'm not sure if this approach will work.

Could someone help me with this please?
 
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  • #2
jgens said:

Homework Statement



Suppose [itex]0 < p < 1[/itex]. Define [itex]b(n,k) = \binom{n}{k}p^k(1-p)^k[/itex]. For what value of [itex]k[/itex] is [itex]b(n,k)[/itex] a maximum?

Homework Equations



N/A

The Attempt at a Solution



Is there any way to get a nice closed form solution to this problem? I've already proved that it has a maximum so there must be some j such that [itex]b(n,j)[/itex] is maximal. Then we know [itex]b(n,j+1) < b(n,j)[/itex] and [itex]b(n,j-1) < b(n,j)[/itex]. And I figure we can use these relations to figure out j or something like that. But I'm not sure if this approach will work.

Could someone help me with this please?

Develop an expression for r(j) = b(n,j+1)/b(n,j) [which, by the way, is also useful for computing the b(n,k) recursively]. What can you say if r(j) > 1? If r(j) < 1?

RGV
 
  • #3
Well, if I let [itex]j[/itex] be such that [itex]b(n,j)[/itex] is maximal, then

[tex]b(n,j-1) < b(n,j) \implies 1 < \frac{b(n,j)}{b(n,j-1)} \implies 1 < \frac{p}{1-p}\frac{\binom{n}{j}}{\binom{n}{j-1}}[/tex]

[tex]b(n,j+1) < b(n,j) \implies \frac{b(n,j+1)}{b(n,j)} < 1 \implies \frac{p}{1-p} \frac{\binom{n}{j+1}}{\binom{n}{j}} < 1[/tex]

But I'm still not sure where to go from here. Do you think you could give me another hint in the right direction?
 
  • #4
jgens said:
Well, if I let [itex]j[/itex] be such that [itex]b(n,j)[/itex] is maximal, then

[tex]b(n,j-1) < b(n,j) \implies 1 < \frac{b(n,j)}{b(n,j-1)} \implies 1 < \frac{p}{1-p}\frac{\binom{n}{j}}{\binom{n}{j-1}}[/tex]

[tex]b(n,j+1) < b(n,j) \implies \frac{b(n,j+1)}{b(n,j)} < 1 \implies \frac{p}{1-p} \frac{\binom{n}{j+1}}{\binom{n}{j}} < 1[/tex]

But I'm still not sure where to go from here. Do you think you could give me another hint in the right direction?

Sure. Work at simplifying the ratio.

RGV
 
  • #5
Okay, so I think I've got it. Rather than TeX the whole thing out right now, is the answer [itex]j < p(n+1) < j+1[/itex] correct?
 
  • #6
jgens said:
Okay, so I think I've got it. Rather than TeX the whole thing out right now, is the answer [itex]j < p(n+1) < j+1[/itex] correct?

OK, if you replace [itex] < [/itex] by [itex] \leq[/itex].

RGV
 

FAQ: Maximizing b(n,k) in Bernoulli Trials Homework

What is the purpose of maximizing b(n,k) in Bernoulli Trials?

The purpose of maximizing b(n,k) in Bernoulli Trials is to determine the probability of getting exactly k successes in n independent binary trials, where each trial has a constant probability of success. This can be useful in various fields such as statistics, psychology, and economics.

How is b(n,k) calculated?

b(n,k) is calculated using the formula b(n,k) = nCk * p^k * (1-p)^(n-k), where n is the total number of trials, k is the number of successes, and p is the probability of success in each trial.

What factors affect the value of b(n,k)?

The value of b(n,k) is affected by the total number of trials (n), the number of successes (k), and the probability of success (p). Additionally, the value of b(n,k) will be higher when n and k are larger, and when p is closer to 0.5.

How can b(n,k) be maximized in Bernoulli Trials?

In order to maximize b(n,k) in Bernoulli Trials, it is important to choose the appropriate values for n, k, and p. For example, increasing the number of trials (n) and the number of successes (k) will typically result in a higher value of b(n,k). Additionally, choosing a value of p that is closer to 0.5 will also increase the value of b(n,k).

What are some real-life applications of maximizing b(n,k) in Bernoulli Trials?

Maximizing b(n,k) in Bernoulli Trials has various real-life applications, such as predicting the probability of a successful outcome in a series of independent events. For example, it can be used to determine the likelihood of winning a game based on the number of attempts and the probability of winning each attempt. It can also be used in market research to predict the success of a product launch based on previous sales data.

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