Example: Cell A versus Cell B strength variation
45 independent pouch-strength readings per packaging cell. Sample 1 is Cell A and Sample 2 Cell B.
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 Variance ratio (F) 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. Keep the full precision shown for standard deviations. No worksheet columns are assigned.
Enter 45 in Sample size (n₁).
Enter 45 in Sample size (n₂).
Enter 1.053112894079627 in Sample standard deviation (s₁).
Enter 1.543914152111739 in Sample standard deviation (s₂).
Sample 1 is Cell A; Sample 2 is Cell B.
4. Run analysis
Choose Run analysis, then open Results.
5. Interpret results
Identify what the interval estimates
45 independent pouch-strength readings per packaging cell. Sample 1 is Cell A and Sample 2 Cell B. The selected parameter is Variance ratio (F).
Read the estimate and bounds
Cell A variance divided by Cell B variance is 0.4653, with a 95% interval of 0.2557–0.8467. The ratio has no unit.
Keep the interpretation clear
The entire interval is below 1, supporting lower variation in Cell A under normal-population and independence assumptions. This is a ratio of variances, not standard deviations.
Use the uncertainty in the decision
Check material, sampling and measurement conditions before attributing the difference to the packaging cell. The result compares spread, not mean strength.
More details: read each result section
Complete result tables use six significant digits, as in Help.
Confidence interval
Parameter names the population quantity. Confidence level 0.95 means this interval method covers the fixed population parameter in 95% of repeated comparable samples under its assumptions. Estimate is the sample-based value; Lower bound and Upper bound mark its uncertainty. Method records the calculation. The entire interval is below 1, supporting lower variation in Cell A under normal-population and independence assumptions. This is a ratio of variances, not standard deviations.
| Statistic | Value |
|---|---|
| Parameter | Variance ratio (F) |
| Confidence level | 0.95 |
| Estimate | 0.465268 |
| Lower bound | 0.255683 |
| Upper bound | 0.846652 |
| Method | F-based |
6. Create a report
Keep the complete Confidence interval table, selected parameter, confidence level, method and entered summaries. The entire interval is below 1, supporting lower variation in Cell A under normal-population and independence assumptions. This is a ratio of variances, not standard deviations.
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.