Hypothesis Testing (Non-Parametric) · TOOL GUIDE

Normality Screening

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Understand the method. Use it with confidence.

Screen all numeric columns for normality and distribution-shape warnings. Quantly runs the method against your active analysis context and returns structured results for review and interpretation.

01

When to use it

Use this tool for rank-, count-, or distribution-based comparisons when parametric assumptions are unsuitable or variables are categorical/ordinal.
Use it only when the selected variables and study design match the method's requirements.

02

How to use it

  1. Open the tool from the Quantly Tools panel.
  2. Confirm the active dataset and analysis session.
  3. Set Numeric Columns (Optional): Select numeric columns to screen. Leave blank to screen all numeric columns.
  4. Set Significance Level (Optional): Threshold for flagging a non-normality signal.
  5. Set Maximum Columns (Optional): Maximum number of numeric columns to screen in one run.
  6. Review optional or advanced settings and keep defaults unless your design requires a change.
  7. Run the tool, inspect warnings and diagnostics, then save or export the result with its assumptions.
03

How to interpret results

Interpret the test statistic and p-value with an effect-size measure where available. A significant result indicates evidence of a difference or association, not its practical size or causal direction.