Basically, we have a population of 4,392 documents and we want to find out the number of patents per document. We don’t want to go through all 4,392 documents, but want a reliable sample size from which to draw inferences. I feel like this count data will not follow a normal distribution, but more like a Poisson (skewed right.) The problem is we don’t have much similar data to this data set, so mean and standard deviation are unknown. Is there any way to derive a sample size based off the confidence interval, margin of error, and population size for what I assume to be a non-normal population? Any help would be greatly appreciated. -- View this message in context: http://r.789695.n4.nabble.com/Sample-size-calculation-for-non-normal-population-with-unknown-mean-and-SD-tp2302833p2302833.html Sent from the R help mailing list archive at Nabble.com.
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