Binomial Distribution and Selection of Suitable Values

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Discussion Overview

The discussion revolves around the selection of appropriate central tendency and variability measures for binomial distributions. Participants explore how to determine which values best describe the data, particularly in the context of estimating parameters for a binomial model based on observed outcomes.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant inquires about the best central tendency and variability measures for a binomial distribution, specifically in the context of observed "yes" and "no" responses.
  • Another participant questions the intent behind the inquiry, asking whether the goal is to confirm the distribution as binomial or to estimate its parameters.
  • A further response emphasizes the need to define what is meant by "best" in the context of estimators for the binomial distribution, suggesting that clarity on this term is crucial for a precise mathematical discussion.
  • Participants discuss the concept of estimators, noting that they can vary based on the sample data and that different criteria (such as maximum likelihood, unbiasedness, and minimum variance) can define what makes an estimator "best."
  • There is a suggestion that if the focus is solely on the mean and variance of the binomial distribution, separate estimators for those parameters should be considered, even though they are functions of the probability parameter p.

Areas of Agreement / Disagreement

Participants express varying views on the definitions and implications of "best" estimators, indicating that there is no consensus on the appropriate measures for central tendency and variability in this context. The discussion remains unresolved regarding the specific methods to be used.

Contextual Notes

The discussion highlights the importance of defining terms and conditions when discussing estimators, as well as the dependence of estimators on the random nature of sample data. There is an acknowledgment that the choice of estimator may vary based on the specific goals of the analysis.

Soaring Crane
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For binomial distributions, how can you tell which central tendency value (mean, median, or mode) and which variability value (interquartile range, variance, standard deviation, etc.) are most appropriate for the data?

Thanks for any reply.
 
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Hey Soaring Crane.

What exactly are you trying to do? Are you trying to see if a distribution is binomial? Are you assuming its binomial to estimate its parameter?

Binomials are good for modelling sums of I.I.D Bernoulli (Yes/No, On/Off etc) type stochastic processes (i.e. random processes).
 
Thanks for replying. I am assuming it is binomial (yes/no reply), but I don't know how to determine which values regarding central tendency and variability describe it best. (For example, there are about ten "no" replies and fourteen "yes" replies.)
 
Soaring Crane said:
which variability value (interquartile range, variance, standard deviation, etc.) are most appropriate for the data?

I think what you are asking is:

Given the data, what is the best method for estimating the parameter of the binomial distribution that fits it?

This is not a precise mathematical question until you define what "best" (or "appropriate") means.

In mathematical terms, you are seeking an "estimator" (i.e. an algorithm or formula whose input is the sample data and whose output is an estimate of the parameter p (the probability of "succsess") that defines a binomial distribution.) An estimator depends on the random values in a sample so the estimator is a random variable. Thus there is no guarantee the estimator will always be close to value you want to estimate. To say what a "best" estimator is, you must be specific about "best" means in scenario that involves random outcomes. Some common ways of expressing human tastes for "best" estimators have the technical names: "maximum liklihood", "unbiased", "minimum variance", "consistent".

So, to ask a question that has a mathematical answer, you should ask questions like:

"What is a maximum liklihood estimator for the parameter p of a binomial distribution?"

"Is there an estimator of the parameter p of a binomial distribuion that is both unbiased and has minimum variance?"

Some forum member can answer those, or you can find the answers on the web, now that the right jargon is established.

Edit: Or perhaps you don't care about p, but only about the mean and variance of the binomial distribution. In that case you should ask for estimators of those parameters. (Even though the mean and variance are both functions of p, a "best" estimator of p is not necessarily a "best" estimator of the mean or variance.)
 

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