One-sample t test
Purpose
Test a mean against a reference or compare two means.
Data and assumptions
Distinguish independent participants from paired measurements. With small samples, assess the relevant distribution and outliers. Specify a one-sided direction before inspecting results.
Configure this method
Choose outcomes and a reference value, such as the neutral score 3. The difference is sample mean minus reference; greater/less alternatives follow that direction.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Test value | Set as needed | 0 |
| Alternative hypothesis | Two-tailed, Greater Than, Less Than | two-sided |
Analysis parameters remain visible in the main configuration area. Advanced formatting contains only the table title and numeric decimals. Methods that calculate intervals also show the significance level; 0.05 corresponds to 95% intervals.
Read the results
Read the direction and confidence interval of the difference before t, degrees of freedom, p and effect size. A nonsignificant result does not establish equivalence. Sample and distribution diagnostics remain in raw output.
Workflow and exports
- Upload the dataset and choose the method from the sidebar or search.
- Select the variables above, set the design-specific options, then run the analysis.
- Inspect the paper-style result. Reconfigure from the result area, or open raw output for diagnostics and sample details.
- Rename and keep result tabs as needed. Export Word, Excel, CSV or TXT; batch export can include the selected AI interpretation. Word retains figures. AI text should be checked against the estimates.