I would like to run some descriptives of some model variables for subsequent modelling in a dataset that uses complex survey design with probability weights. In particular, I would like to see the skewness, kurtosis, and quantiles of a variable along with a histogram of the results. Normally, I would use
Code:
sum y, d
Code:
histogram y, normal
BTW (I hope it's ok to ask a related question) when I plot the histogram using fweight (because pweight is not available), to attempt to do this, I find that the total AUC of the normal density curve can be much greater or less than that of the actual distribution. This does not seem to make sense to me?
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