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If I have 1,000 participants ranking on a scale of 1 to 10 regarding some object how do I interpret the confidence level and margin of error of the resulting rank? I am used to of seeing 99% confidence level and 4% margin of error type notations so how do these numbers play into my sample case? And how does the resulting rank fit with the large n and Central Limit Theorem?

I am weighting each rank against the percentage of total participants to get a final result.

And could you also explain what a response distribution is related to this scenario and why it is best to assume 50%?

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    from wikipedia: >central limit theorem (CLT) states that, given certain conditions, the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed.[1]2012-10-29

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Your question is a little vague, but essentially standard error, standard divination, etc. become negligible when the sample size is sufficiently large. The standard error is equal to the standard deviation divided by the square root of the sample size, which is a result from CLT.

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    What does the margin of error apply to? and How (some explanation here maybe) is the central limit theorem fulfilled in this case?2012-10-29
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    You should rephrase your question before you downvote my answer. Like I said, your standard error is small because your sample size is large.2012-10-29
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    @glebovg I also am a bit unclear of why a certain standard of error is required, there is a relationship that if the number of samples increases then the error goes down. Is this what the asker is after?2012-10-29
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    @MaoYiyi To be honest, I am not sure what the question is.2012-10-29
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    I did not down vote the answer (I don't even have the points) however I think I am beginning to understand and recall some of what you mention. Obviously, I am a bit rusty. What I was wondering if I weight the rankings each person gives from the sample and get a number then that result must be within a MOE from the actual response from the population and have a 99 CL. How that response fits in with CLT was the other half. If n is high then how does that affect how I interpret the MOE, if any.2012-10-29
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    If $n$ is large, margin of error should be small that is all I can tell you. I am still confused.2012-10-29
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    @nvdkgm what exactly do you want, in plain english (or which language you perfer). CLT in a nut, says more samples less error provideded certain conditions exist, to be over basic. Do you want to know if your sample is large enough to have less than 4% error?2012-10-30
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    @glebovg at least we know the answer is 42. hehe2012-10-30