Jay Warner wrote:
>
> If the distribution is monomodal, not bounded (one peak, tails on both
> sides), and within some rational range of a Normal, then a transformation
> can be performed to make it look 'Normal.' See the Johnson transformation
> in some commercial stat packages.
>
> The next question is why would you bother? Looks pretty, feels more
> comfortable to one with experience only with Normal dist.'s, but once you
> know the transformation there is no greater or less amount of information in
> it, as I understand such things.
One good reason: knowing the transformation that symmetrizes the
distribution can give a useful description of the distribution. For
instance, if you know that a log transformation renders a data set
approximately normal, then you can conjecture that the process that
generates the variation within it is essentially multiplicative.
*No* transformation can add information content to a data set; but that
is not what transformations are for.
-Robert Dawson
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