5. How do you sum up a distribution of values?
The first parameter that comes to mind when summing up a random phenomenon is the mean. The mean is a so-called positional parameter, because the possible realizations of the phenomenon will be positioned at a point on the scale of values, "in the vicinity" of this parameter. For example, when a measurement error is corrected, the random phenomenon has a mean of zero, whereas when the measurement error is not corrected and reveals a significant bias, the mean is no longer zero. Although the shape of the distribution of values may be the same in these two cases, a histogram representing the random phenomenon will be "positioned" in two different places.
There are other position parameters than the average:
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How do you sum up a distribution of values?