Shapiro Wilk test for Normality

Does anyone know how to do or create a function for the Shapiro Wilk test in Igor?
To properly implement the Shapiro-Wilk test you would need code equivalent to Algorithm R94 [Appl. Statist. (1995) Vol. 44, 4]. If you are comfortable with compilers, you can either compile the Fortran code or use f2c and then compile the C code. Converting this into IGOR code is possible but not trivial.

Sorry to dig this up.

But is there any chance, that this widely-used Test may be implemented in any future Igor version?
Irvine_audit wrote:
Sorry to dig this up.

But is there any chance, that this widely-used Test may be implemented in any future Igor version?


More than a chance, it is in IP7 as StatsShapiroWilkTest.

A.G.
WaveMetrics, Inc.

For v.8, does functionality exist for alpha values other than the default, which I assume is 0.05?  If not (yet) is there a dirty way in which to effect this?

I think there is a misunderstanding here that may be due to the examples in the documentation.  The test as implemented returns two values: V_statistic and V_prob.  At this point there is no assumption about alpha.

After you execute the operation you compare V_prob to the desired alpha value and if V_prob<alpha you reject the null hypothesis that the population is normally distributed.  I see no point in adding an alpha input to perform the test V_prob<alpha.

The examples in the documentation are somewhat extreme in that p=0.846139 is simply likely to be larger than any practical value one might use for alpha and p=1.7979e-05 is likely smaller than typical alpha values.

A.G.