Finding a Minumum N from Binomial Distribution

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  • #1
Youngster
38
0

Homework Statement



From the text: Use Hershey's Kisses to estimate the probability that when dropped, they land with the flat part lying on the floor. How many trials are necessary to get a result that appears to be reasonably accurate when rounded to the first decimal place?

Homework Equations





The Attempt at a Solution



Well assuming that I already obtained some ration through a numerous amount of trials ( by the Law of Large Numbers), how would I use that value to obtain a minimum N amount of trails necessary to get a reasonably accurate result?

I know that the Binomial Probability Formula is:

P(x) = [itex]\frac{n!}{(n-x)!x!}[/itex] [itex]\bullet[/itex] px [itex]\bullet[/itex] qn-x

How would one isolate n in that formula though? Or should I approach this a different way?
 
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  • #2
The wording of this problem implies that they expect you to actually do this experiment, using Hershey Kisses, then use the data from your experiment.
 
  • #3
HallsofIvy said:
The wording of this problem implies that they expect you to actually do this experiment, using Hershey Kisses, then use the data from your experiment.

You will also need to decide what is meant by "appears to be" and "reasonably accurate". (These would be issues on which people can honestly disagree!)

RGV
 

FAQ: Finding a Minumum N from Binomial Distribution

What is the definition of "minimum N" in the context of binomial distribution?

The minimum N in binomial distribution refers to the smallest number of trials required to achieve a certain level of probability or confidence in an outcome. It is often used in statistical analysis to determine the minimum sample size needed to make accurate conclusions about a population.

How is the minimum N calculated in binomial distribution?

The minimum N can be calculated using a formula that takes into account the desired level of probability, the expected success rate, and the degree of precision desired. This formula is known as the minimum sample size formula and is commonly used in statistical software programs.

What factors influence the minimum N in binomial distribution?

There are several factors that can influence the minimum N in binomial distribution. These include the desired level of probability, the expected success rate, the degree of precision desired, and the variability of the data. In general, a higher level of probability or a lower degree of precision will require a larger minimum N.

Why is it important to determine the minimum N in binomial distribution?

Determining the minimum N in binomial distribution is important because it allows researchers to determine the appropriate sample size needed to make accurate conclusions about a population. This helps to ensure that research findings are reliable and can be generalized to a larger population with a certain level of confidence.

Are there any limitations to using the minimum N in binomial distribution?

Yes, there are limitations to using the minimum N in binomial distribution. This method assumes that the data follows a binomial distribution, which may not always be the case. Additionally, it does not take into account other factors that may affect the accuracy of the results, such as sampling bias or measurement error.

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