Example: Cell A versus Cell B mean strength
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 Difference between means for Parameter. Enter 0.95 in Confidence level (0–1) for a 95% interval.
3. Enter the summaries
Under Summarized data, enter these full-precision values. No worksheet columns are assigned.
| Input field | Cell A — sample 1 | Cell B — sample 2 |
|---|---|---|
| Sample size | Sample size (n₁): 45 | Sample size (n₂): 45 |
| Sample mean | Sample mean (x̄₁): 17.988222222222223 | Sample mean (x̄₂): 18.455333333333332 |
| Sample standard deviation | Sample standard deviation (s₁): 1.053112894079627 | Sample standard deviation (s₂): 1.543914152111739 |
Leave Assume equal variances unchecked. Choose Integer — validation dataset convention for Degrees of freedom. This option rounds the calculated degrees of freedom down; here, 77.6576 becomes 77.
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 difference between means.
Read the estimate and bounds
Cell A minus Cell B is −0.4671 N, with a nominal 95% interval of −1.0219 to +0.0876 N. A negative value means Cell A has lower average strength.
Keep the interpretation clear
The Welch interval crosses zero, so the study does not establish different means. It also does not establish equivalence. This example truncates 77.6576 Welch degrees of freedom to 77.
Use the uncertainty in the decision
Define the smallest mean-strength difference that matters. Compare the whole interval with it before deciding whether the study is precise enough.
More details: read each result section
Complete result tables use six significant digits, as in Help.
Confidence interval
Parameter names the population quantity. This Welch interval has a nominal 95% confidence level; coverage is approximate under its assumptions. Estimate is the sample-based value; Lower bound and Upper bound mark its uncertainty. Method records the calculation. The Welch interval crosses zero, so the study does not establish different means. It also does not establish equivalence. This example truncates 77.6576 Welch degrees of freedom to 77. DF convention, Unrounded Welch DF and DF used document the integer Welch calculation.
| Statistic | Value |
|---|---|
| Parameter | Difference between means |
| Confidence level | 0.95 |
| Estimate | -0.467111 |
| Lower bound | -1.02187 |
| Upper bound | 0.0876452 |
| Method | Welch (unequal var) |
| DF convention | Integer — validation dataset convention |
| Unrounded Welch DF | 77.6576 |
| DF used | 77 |
6. Create a report
Keep the complete Confidence interval table, selected parameter, confidence level, method and entered summaries. The Welch interval crosses zero, so the study does not establish different means. It also does not establish equivalence. This example truncates 77.6576 Welch degrees of freedom to 77.
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.