Normal Q-Q and P-P plots (plain and detrended)
Compares the data with a normal distribution: points on the straight line mean normal data. The detrended plot shows the deviations from the line. Plotting positions follow SPSS (Blom, ties get the mean rank).
Menu: Graphs → More charts → Normal Q-Q / P-P plots…
When should I use it?
- Checking the normality assumption more precisely than a histogram.
What are the assumptions?
- A scale variable.
How do I run it in StatLab?
- Choose the variables and Q-Q or P-P; keep the detrended plot.
How do I read the output?
| Output | Meaning |
|---|---|
| Q-Q | Observed value against expected normal z. |
| P-P | Observed against expected cumulative probability. |
| Detrended | Deviation from the line; a pattern (curve, S shape) means non-normal. |
Worked example
On the practice survey dataset (File → Sample dataset), this command — which the dialog's Paste button also produces — runs the procedure:
PROC vizQQ /vars=(score age) /kind=qq /detrended=YES.
Computed by StatLab's validated procedure code when this page was built. The example only illustrates the steps; choose variables that fit your own research question.
What are common mistakes?
- Worrying about a few wobbly points in the tails with large samples.