Hi All Is it possible to generate a sample that has a specific mean, SD (also skewness, kurtosis)? To be more specific, I do not want to sample from a given distribution (like the normal distribution) that has a specific mean and SD. If sampled from a normal distribution with a given mean and SD, of course the mean of the sample is not the exact same as the mean of the normal distribution. I try to get a sample that has a previously given mean and SD (and also if possible skewness and kurtosis).
Does anybody know the mathematical approach to this question? And, does anybody know a software package that does this perhaps, or an algorithm to use to program my own thing? Some vague things, like moments, are in my head but that is perhaps not the correct path. Others asked, expressed it this way: Sampling from a normal distribution with restriction (restriction that the mean is exactly the given mean). Thanks Toby mean = (sum xi) / N variance = (sum (xi - mu) ^ 2) / N skewness = (sum (xi - mu) ^ 3) / (N sdev ^ 3) kurtosis = (sum (xi - mu) ^ 4) / (N sdev ^ 4) . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
