MrDavid (02-06-2017)
hi,
if I understand you correctly you have many data points but they refer to different groups, so you have a small number of data per group? And you need a model per each group?
There is a saying that a small dataset is always normally distributed, a large one never is - this means that the power of the normality tests is such, that they will pretty much always fail to reject the null for a small dataset. So, running the tests for small groups is not going to help you, except in really extreme cases, as has already been pointed out here. Depending on what you need to do, you might want to consider simply using your data to make predictions (as in boostraping, by creating larger samples by sampling with replacement from your original data). That could give you an idea of how often the demand would exceed a given limit, for example.
regards
MrDavid (02-06-2017)
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