Hello,
I have data which correspond to different cases (resistance values for different structures). I want to make the normal quantile plot for each case and see all cases in the same graph (each case with different marker or color, for example) in order to observe directly the differences and make comparisons.
Is it possible? I try grouping by structure in the option "by" but I obtain one different graph for each case.
Kind regards,
G.
This result is possible in the Oneway platform. I assume that you have the data in one column and the group indicator in another column. Select Analyze > Fit Y by X. Select the data column and click Y. Select the column with the group indicator and click X. Click OK to launch Oneway.
Click the red triangle next to Oneway and select one of the commands to plot the normal quantiles.
Note that you can also select Rows > Color or Mark by Column and select the grouping column. This command (by default) will assign the same color to markers as used for the lines for each group.
This result is possible in the Oneway platform. I assume that you have the data in one column and the group indicator in another column. Select Analyze > Fit Y by X. Select the data column and click Y. Select the column with the group indicator and click X. Click OK to launch Oneway.
Click the red triangle next to Oneway and select one of the commands to plot the normal quantiles.
Note that you can also select Rows > Color or Mark by Column and select the grouping column. This command (by default) will assign the same color to markers as used for the lines for each group.
Hi - thanks for the response. I'm not sure why you are discounting the use of a normal quantile plot for nested groups. I would like to put all the groups together for visual comparison on the same plot. Plots like this are common to compare the distribution of a certain parameter across different experiments.
Here's a visual of what I'm trying to achieve:
No offence taken and none intended.
Not sure why you are assuming there is a time-effect. There is no time-variable here. They are distributions which don't necessarily have to affect each other. They are nested for the purpose of grouping them. They are compared by looking at the distributions themselves within each sub-group. By looking at the distribution, I am not throwing out any information. Maybe I am missing your point? In any case, I am wondering how such a Q-Q plot could be made.
@shrirams, I have thought about your situation and the plots you are looking to create. The diagram you show appears that those components A & B are not nested, but crossed! Every level of A sees every level of B. It seems to me that you are running experiments nested "inside" those components. This to me sounds like replicates. The A & B components are either creating 4 blocks (If A & B are noise) or the whole plot (if A & B are design factors) of a split-plot design. Are these components noise variables or design factors? In any case, if you are trying to create normal plots for each Block or Whole plot, I have a less than elegant way of doing this. If my interpretation is correct, I can give you guidance as to how to get JMP to do assist in performing this analysis.
@statman Yes indeed, the factors are crossed and not nested. And as you pointed out, I'm looking at the distribution of the replicates. The nesting occurs in the split-plot. In my case, A & B are not noise variables, but rather design factors. Pointers to create such a plot will be very helpful.