[SciPy-user] normalizing data/distributions

[A.J. Rossini]

"Scott Bray" <scottbray83 at hotmail.com> writes:

> i am working on a statistics type project for university study. i have
> a set of data, have built a discrete probability distribution from
> this data (using the cauchy distribution) and now want to normalize
> it. currently, the area of the distribution is not equal to one. i
> have been trying to find literature about how to normalize, but have
> been unsuccessful (and what i have found, i am unsure on the
> validity). some say to normalize the data points by:
>
> (data point - sample mean) / sample std

This is to "normalize" it in the sense of making it match a N(0,1)
distribution -- you explicitly said that you were using a cauchy as
the basis?!

> others say to multiply by a normalising constant that is "chosen" to
> make the area equal to one. i tried this by just scaling the area to
> equal one.

This is probably the most reasonable approach to making a
"distribution" of your discretized empirical observations.

best,
-tony

-- 
rossini at u.washington.edu            http://www.analytics.washington.edu/ 
Biomedical and Health Informatics   University of Washington
Biostatistics, SCHARP/HVTN          Fred Hutchinson Cancer Research Center
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