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I guess you are talking about residual plots for linear regression in which case you will have to form the residuals 鈥渂y hand鈥� using the Manipulate Variables menu

Suppose that you were predicting height from age:

1. Drag variable names to produce the height vs age聽 scatter plot
2. Use Add to Plot to put a linear trend on it
3. Click Get Summary (or Get Inference) to obtain the intercept and slope from the fitted line. Suppose it turns out:聽 int=96.71 slope = 4.83
4. Use 鈥淐reate New Variables鈥� which is under 鈥淢anipulate Variables鈥�.
5. For understandability I鈥檇 do it in 2 steps 鈥�
   a.聽 Create PredHeight = 96.71 + 4.83*age
   b.聽 Create Resids = height 鈥� PredHeight

Then you can plot Resids against anything you like聽 (in iNZight all variable names are case sensitive)

I didn鈥檛 get this 鈥渃anned鈥� in the basic part of iNZight because in a bivariate setting (a single predictor variable) you seldom see anything in a residual plot you can鈥檛 see in the original scatter plot so I would not stress residual plots in a first bite at regression (except maybe for your brighter students).

If you turn them loose on the Model Fitting module under 鈥淎dvanced鈥� then residual plots are generated automatically but that part was really designed for university courses.