Abstract
The validity of the normal distribution as an error model is commonly tested
with a (half) normal probability plot. Real data often contain outliers. The use of
t-distributions in a probability plot to model such data more realistically is
described. It is shown how a suitable value of the parameter of the
t-distribution can be determined from the data. The results suggest that even
data that seem to be modeled well using a normal distribution can be better
modeled using a t-distribution.
| Original language | Undefined/Unknown |
|---|---|
| Pages (from-to) | 319-321 |
| Number of pages | 3 |
| Journal | Acta crystallographica. Section A, foundations of crystallography |
| Volume | A65 |
| Publication status | Published - 2009 |