Example: Cell A leak-test pass proportion
470 of 500 independently tested Cell A pouches passed the leak test. The reference CSV also lists Cell B’s separate sample.
Download the study reference (CSV)This is the same example used in Help. The CSV is a reference for the supplied study. Enter the checked summaries manually on Inputs; importing the CSV does not populate this calculator. Use Open example in a practice copy in Help to prefill the inputs.
1. Create the workspace
In the sidebar, open Basic Statistics and choose Confidence Intervals. Create an analysis, name it, select New blank worksheet, then choose Create analysis.
2. Choose the interval
On Inputs, choose Proportion for Parameter. Enter 0.95 in Confidence level (0–1) for a 95% interval.
3. Enter the summaries
Under Summarized data, enter the following values. No worksheet columns are assigned.
Enter 500 in Number of trials (n).
Enter 470 in Number of events (x).
Choose Exact (Clopper–Pearson) for Proportion method and leave Sample proportion (p̂) blank. The event count takes precedence.
4. Run analysis
Choose Run analysis, then open Results.
5. Interpret results
Identify what the interval estimates
470 of 500 independently tested Cell A pouches passed the leak test. The reference CSV also lists Cell B’s separate sample. The selected parameter is proportion.
Read the estimate and bounds
The observed pass proportion is 470/500 = 0.94, or 94%. Its exact nominal 95% interval is 0.91545–0.95916, or about 91.55–95.92%.
Keep the interpretation clear
This interval concerns the population leak-test pass proportion. It does not describe the strength measurements or guarantee a required pass rate. Events here are passed tests, not failures.
Use the uncertainty in the decision
Compare the whole pass-rate interval with the applicable requirement, not just the observed 94%. Keep the sampling method and pass definition with the result.
More details: read each result section
Complete result tables use six significant digits, as in Help.
Confidence interval
Parameter names the population quantity. The nominal confidence level is 95%. Under an independent binomial model, Clopper–Pearson coverage is at least that level and can be conservative because counts are discrete. Estimate is the sample-based value; Lower bound and Upper bound mark its uncertainty. Method records the calculation. This interval concerns the population leak-test pass proportion. It does not describe the strength measurements or guarantee a required pass rate. Events here are passed tests, not failures.
| Statistic | Value |
|---|---|
| Parameter | Proportion |
| Confidence level | 0.95 |
| Estimate | 0.94 |
| Lower bound | 0.915451 |
| Upper bound | 0.959156 |
| Method | Clopper–Pearson (exact) |
6. Create a report
Keep the complete Confidence interval table, selected parameter, confidence level, method and entered summaries. This interval concerns the population leak-test pass proportion. It does not describe the strength measurements or guarantee a required pass rate. Events here are passed tests, not failures.
Choose Add to report from the completed run. Open Choose individual items and advanced options to select tables and charts, then choose Add to draft. Hidden items stay in the saved analysis.
Name the report and add the purpose of the study and your interpretation. Choose Save, review Preview, then use Export → Download HTML. The example below contains the full selected content, including results beyond one screen.