Overall descriptive statistics
Purpose
Summarize levels, dispersion and ranges of numerical measurements.
Data and assumptions
Select meaningful numerical variables. A mean of category codes is usually not interpretable. Each variable uses its available observations.
Configure this method
Choose summary measures in analysis settings. Rows correspond to variables; kurtosis is excess kurtosis. Missing values are excluded separately per variable, so differing Ns do not define one common sample.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Descriptive statistics | N, Mean, Standard deviation, Median, First quartile, Third quartile, Min, Max, Skewness, Kurtosis | ['n', 'mean', 'sd', 'median', 'min', 'max'] |
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
N is the valid sample size for that row. Report mean and standard deviation for reasonably symmetric distributions and median and quartiles for skewed distributions.
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.