When a data-set is normally distributed, we have lots of tools at our disposal to analyse the data. However, this is not the case when data is not normally distributed.
What are some methods for working with data that is not normally distributed? And even if there is a way to do this, how would the outline of the methods work? I am also wondering when these methods would be appropriate to use, like as in what sort of cases?
I did hear that "t-tests" are a good way of analysing non-normal data, but I could not find a simple explanation as to why? I also heard of other methods such as the "sample - sign test" or the "run chart" however, I am not too sure how they are able to analyse non-normal data either.