Hello Everyone,
Does anyone know how to implement manual calculation of the Shapiro-Wilk test statistic in JMP?
Using JSL script and/ or column formulas?
I know that JMP natively does this calculation natively in Analyze>Distribution and then Continuous Fit>Normal>Goodness of Fit, but I'm trying to reproduce the calculated value of the test statistic in order to understand it's basis with greater depth.
There are a number of useful clues in references online, but I'm having some difficulty putting the pieces together:
https://en.wikipedia.org/wiki/Shapiro%E2%80%93Wilk_test#cite_note-8
Here's the basis for it summarized nicely from Wikepedia link above:
Also some helpful clues here using MS Excel.
@PatrickGiuliano I am not sure why you would want to do this manually, when you have JMP that can produce the statistics and you can extract it from a report. A simulation where the sample size is the same so the weight coefficients are the same, meaning the weights are calculated once and used many times, might be a good scenario for doing this by hand/matrix.
That said, I found references for the coefficients and an algorithm to get them. The references are reported in the attached script. Here are the results of two tests with N=40.
Here is a link that does a step by step calculation that you might be able to use.
http://blog.excelmasterseries.com/2015/05/how-to-create-completely-automated_4.html
Ignore this...I did not read your request very closely...sorry
JMP calculates the Shapiro-Wilk's test.
The test is available in JMP PRO 12 and higher.
It is the Goodnes of Fit test for a Normal Fit. The JSL is
Distribution(
Continuous Distribution(
Column( :height ),
Fit Distribution( Normal( Goodness of Fit( 1 ) ) )
)
);
@PatrickGiuliano I am not sure why you would want to do this manually, when you have JMP that can produce the statistics and you can extract it from a report. A simulation where the sample size is the same so the weight coefficients are the same, meaning the weights are calculated once and used many times, might be a good scenario for doing this by hand/matrix.
That said, I found references for the coefficients and an algorithm to get them. The references are reported in the attached script. Here are the results of two tests with N=40.