I am looking at data set that has four groups. In each group, the data is mostly, 99+% of time, composed of zeros, but, when it is not zero it can be any float number (e.g., 0.01 to 921.2, with most values being under 10). Once I examine dataset 1, I want to examine other datasets that also have 4 groups and similar sparseness in the data. Sometimes the n or number of observations in a group can be as low as 10 or as high as, say, 20,000.
I want to calculate a point estimate and confidence intervals (CI) around that estimate for each group so that I can quickly determine whether group 1 is say, worse than group 2.
My question: is it appropriate to calculate the CI using mean and standard error (stdev / sqrt(n) ) with such a sparse data set? Any advice would be appreciated!!