Johnson transform

[#1]

I am trying to find a normalizing transform for my data so that I can model my data with the normal distribution.

I am using Analyze-Distribution by [my product], for all six of my Y variables.

I have two informal criteria:

1. AICc within 5 of the lowest AICc for any distribution for that Y var and product.

2. Shapiro-Wilk W test Prob<W >0.05.

This is telling me that the Johnson SU is overall definitely the best choice.

My question is, how do I tell JMP Fit-Model to use the Johnson SU distribution?  I don't see the distribution option that should be there!  ARRGGGHH.

I am not JSL literate yet.  If I have to do the transforms manually (in Excel), is it as simple as calculating ASINH of each value then copying that into a data table?  Then, on any conclusion, I have to transform back using SINH?  Or is it more complicated?  Do I have to include estimates of each of the four JSU parameters into the ASINH and SINH to do it properly?

[#2 · Accepted solution]

When you are in the distribution platform you can click on the red-triangle and save the transformed data back to the table and model that transformed normal response.