Maybe the most common mistake is omission of graphic eye-balling.
On Thu, 22 Mar 2001, Paul Swank wrote:
> I couldn't help wanting to add my own 2 cents to the discussion about statistical
>errors because I have always thought that people put too much faith in formal tests
>of assumptions. When the tests of assumptions are most sensitive to violations is
>when they are of less concern, when the sample size is large. When the ramifications
>of violating assumptions are greatest, when samples are small, the tests have no
>power to detect violations. There is no substitute for examining your data. If the
>data are badly skewed, you don't need a normality test to tell you that, a simple
>histogram will do it.
>
>
>
> ------------------------------------
>
> Paul R. Swank, PhD.
>
> <smaller>Professor & Advanced Quantitative Methodologist
>
> </smaller>UT-Houston School of Nursing
>
> Center for Nursing Research
>
> Phone (713)500-2031
>
> Fax (713) 500-2033
>
>
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