One-sample nonparametric tests (automatic)
Tests each chosen field against a standard distribution and picks the test from the data: binomial for two categories, chi-square for more categories, Kolmogorov-Smirnov (normal) for scale fields.
Menu: Analyze → Nonparametric Tests → One Sample…
When should I use it?
- Quick screening of several variables at once: are the categories equally common, is this score normal?
What are the assumptions?
- Measurement levels are set correctly in Variable View (nominal vs scale).
How do I run it in StatLab?
- Move the fields to Test fields; set the significance level.
- Tick 'Show the detailed test tables' for the full tables behind each decision.
How do I read the output?
| Output | Meaning |
|---|---|
| Hypothesis Test Summary | One row per field: the null hypothesis, the test used, Sig. and the decision (reject / retain). |
Worked example
On the practice survey dataset (File → Sample dataset), this command — which the dialog's Paste button also produces — runs the procedure:
PROC npOneSample /vars=(q1 q2 q3) /alpha=0.05 /details=NO.
Output tables: Hypothesis Test Summary.
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?
- Leaving numeric codes of a categorical variable as 'scale' — the normality test is then used instead of chi-square.