Q–Q plot generator

Statistical Distribution & Shape

A quantile-quantile (Q-Q) plot assesses whether a dataset follows a given theoretical probability distribution (most commonly the standard normal distribution). It charts the empirical quantiles of your observed data on the y-axis against the theoretical quantiles of the reference distribution on the x-axis. If your data perfectly matches the theoretical model, the plotted points will fall cleanly along a 45-degree reference diagonal line. All statistical computations and rendering are executed entirely locally on your device, ensuring your data remains strictly private without any server uploads.

Data Requirements & Continuous Variables

Format input columns for q–q plot with explicit headers and numerical measurements. Verify that rows represent discrete categories or observations without unformatted symbol artifacts.

Sample Distribution Data

| Observation ID | Residual error |

Guidelines for Interpreting Distributions

• Ensure sufficient visual distinction for q–q plot marks across standard and high-contrast viewports.
• Align text labels horizontally whenever possible to improve cognitive readability for q–q plot elements.
• Double-check scale boundaries and zero-anchors before exporting q–q plot presentation artwork.