Power analysis — proportions
Sample size or power for one proportion against a constant (exact binomial test) or two independent proportions (z test or Cohen's h).
Menu: Analyze → Power Analysis → Proportions…
When should I use it?
- Planning a survey or an A/B test on rates.
What are the assumptions?
- Independent observations.
How do I run it in StatLab?
- Choose the test and give the proportions, α and the target power (or sample size).
How do I read the output?
| Output | Meaning |
|---|---|
| Actual power / Actual α | The exact binomial test cannot hit α exactly; both are shown. |
Worked example
On the practice survey dataset (File → Sample dataset), this command — which the dialog's Paste button also produces — runs the procedure:
PROC pwProportions /mode=n /type=two /p1=0.6 /p2=0.4 /method=z /tails=2 /ratio=1 /alpha=0.05 /power=0.8.
Output tables: Power — two independent proportions, z test (a priori).
How would I report it in APA style?
A sample of 194 gives power .800 to detect the stated effect at α = .050.
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?
- Expecting power to rise smoothly with N for the exact test — it moves in a saw-tooth.