Thank you so much that looks great and works fine with my jmp version! Just one last question, aren't normally the quantiles of the residual on the x-Axis and not the actual residuals?
Julia,
You are correct that most Q-Q plots will use the sample data quantiles on the Y axis and the theoretical distribution quantiles on X-axis. See https://en.wikipedia.org/wiki/Q%E2%80%93Q_plot Also a Q-Q plot typically uses the same scale, since the quantiles of the sample data is plotted against the quantiles of the theoretical, hence, its name.
JMP plots are called probability plots, and the sample (Actual) data scale is used for one axis. The reason, I documented using Fit Y by X is because it allows you to to create an Actual by Quantile or a Quantile by Actual.
If you want a Q-Q plot as documented by the url above, you need to compute the standardized data values, or compute the sample quantile (0 to 1, sort the data and compute the cdf ) and use that data in Fit Y by X, and plot Actual by Quantile and then they will have the same scale.
However, I like the probability plot, because typically the consumer of the reported plot typically relates to actual sample data scale. Also, the key to any probability or Q-Q plot is to asses whether the data appoximates a linear relationship.
Because I first learned to use probability paper in physics prior to the computer age (yes in the late 60's we still used slide rules), plotting Quantile by Actual is my preference. However, I recommend you plot the data in a format that is expected or typical. If there is no "norm" or expectation then just add a blurb to your paper or report, describing the plot.
Hope that helps!
gzmorgan0,
thanks so much for your explanation, I now decided to take the normal probability plots. Just to make sure, on the y-axis there is the normal probability which is at the same time the normal quantiles, right? Also they are general normal quantiles and not in any way modified to fit my data? On the x-axis I put the residuals of a mixed model, so it would not be correct to call the plot a QQ-Plot but only a normal probability plot? Or are the terms not so strict and I could calll that a QQ-Plot, too? Because I feel like my supervisor called that a QQ-plot..
Thanks so much and best wishes,
Julia
Yes, the Y-axis probability and quantiles are those of a normal.
Some people call these JMP plots quantile plots and they serve the same purpose as a Q-Q plot, to check if the distribution of residuals are approximately normal.
You should also plot residuals vs. predicted and residuals vs. x. The residuals should be randomly distributed for all levels of X and predicted.
Regards.