The difference is what was used to make up the distribution.
In a distribution of returns, we are taking all the returns we got from our test (or real life Portfolio) and grouping the returns into bins. We’d call this descriptive statistics because it is describing what happened.
In a sample distribution, we are pulling out a random set of data from the population, measuring it, and putting the results in a distribution. Based on what we see, we “infer” what we expect to be true for the whole population. We call the inferential statistics because we are inferring that or results apply to the population.
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