Proportion Confidence
Interval Tool
Enter data and click calculate to generate statistical insights.
Guide: How to Use
1. Sample Size: Enter the total number of observations in your study.
2. Successes: Enter the specific count of the attribute you are measuring.
3. Confidence: Select your desired level of certainty (95% is industry standard).
4. Population: Only fill this if your sample represents more than 5% of the total population (uses Finite Population Correction).
Critical Facts
Confidence intervals provide a range of values that likely contain the true population parameter. A 95% interval means that if you repeated the study 100 times, 95 of those intervals would contain the real proportion.
Use Cases
- Political Polling: Estimating voter support.
- Quality Control: Defect rates in manufacturing.
- A/B Testing: Conversion rate uplift in marketing.
- Medical Research: Efficacy rates of new treatments.
About the Math
This tool uses the Normal Approximation Method (Wald Interval). It is most accurate when np and n(1-p) are both greater than 5. For very small samples, results may vary slightly from the Clopper-Pearson method.
Practical Example
Imagine you survey 1,000 customers and 600 say they prefer your new logo. Using a 95% confidence level, the tool calculates a proportion of 60% with a margin of error of approx ±3%. You can be 95% confident the true customer preference is between 57% and 63%.
| Feature | Details |
|---|---|
| Price | Free |
| Rendering | Client-Side Rendering |
| Language | JavaScript |
| Paywall | No |
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