What This Calculator Measures
Estimate sampling margin using confidence, standard deviation, and effect size.
By combining practical inputs into a structured model, this calculator helps you move from vague estimation to clear planning actions you can execute consistently.
This calculator estimates margin of error and required samples.
How to Use This Well
- Enter sample size and confidence.
- Add standard deviation and effect size.
- Set population and design effect.
- Review margin and required sample.
- Adjust sample size.
Formula Breakdown
Margin = z x std dev / sqrt(n)Worked Example
- 95% confidence with std dev 12.
- Margin around 2.1.
- Required sample around 62.
Interpretation Guide
| Range | Meaning | Action |
|---|---|---|
| Small margin | Tight. | High precision. |
| Medium margin | Balanced. | Standard precision. |
| Large margin | Wide. | Increase sample. |
| Very large | Loose. | Revisit design. |
Optimization Playbook
- Increase sample: reduce margin.
- Reduce variance: improve precision.
- Adjust design effect: refine assumptions.
- Check effect size: align with goals.
Scenario Planning
- Baseline: current sample size.
- Higher confidence: raise to 99%.
- Smaller effect: reduce effect to 2.
- Decision rule: keep margin under 3.
Common Mistakes to Avoid
- Ignoring design effects.
- Using low sample sizes.
- Overlooking variance.
- Misreading effect size.
Implementation Checklist
- Measure variance.
- Select confidence level.
- Set effect size.
- Review margin.
Measurement Notes
Treat this calculator as a directional planning instrument. Output quality improves when your inputs are anchored to recent real data instead of one-off assumptions.
Run multiple scenarios, document what changed, and keep the decision tied to trends, not a single result snapshot.
FAQ
How do I pick z values?
90% = 1.645, 95% = 1.96, 99% = 2.576.
What is design effect?
It adjusts for complex sampling designs.
Should I include population size?
Include it if sample is a large share of population.