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Overlays in graph builder and of half normal plots

Stuart_Little

Hi all,

I have a customer that is after 2 specific plots that they currently generate in Excel for their data but are proving less straightforward to generate in JMP without performing additional steps that the customer is reticent to do, unless absolutely necessary.

The first problem is how to remove unwanted plots from graph builder overlays. As can be seen in the attached file, the data is currently structured into 6 columns, 3 sets of X data, and 3 sets of Y data. Plotting this in Graph builder gives (unsurprisingly) the 9 possible plots, and the customer just requires the 3 (lo-lo, mid-mid, high-high) plots. Is there a trivial way to remove these plots in graph builder? I’ve already shown how to achieve this via stacking the data into 2 columns, but the customer would prefer to do this in one step from the native data if possible.

The second question was whether it’s possible to readily overlay half-normal plots for easy identification of issues in their data?

Thanks in advance,

Stuart

Example_data_file.jmp

Accepted answers

Chris_Kirchberg

So will something this work:

This is from JMP 16. I can create a new column called cumulative prob from right clicking on the A_ group of data.

All comments

Chris_Kirchberg

@Stuart_Little ,

How do they want the final output to look? 3 Y by X scatter plots in a single column in the graph and then 3 normal quantile plots in a second column?

Stuart_Little

Hi Chris,

I should've been clearer as there's no need for the two plots to be on the same graph.

The first plot that they're after an overlay plot from the data like this one generated via stacking the data.

They also then want an overlay of the half normal plots for the 3 "A" variables - so essentially the overlay of these three plots from the distribution platform:

Thanks,

Stuart

Chris_Kirchberg

So will something this work:

This is from JMP 16. I can create a new column called cumulative prob from right clicking on the A_ group of data.

Stuart_Little

Thanks @Chris_Kirchberg, that's perfect