Shapiro-Wilk and Shapiro-Francia normality tests.
Shapiro-Wilk & Shapiro-Francia parametric hypothesis test of composite normality.
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Shapiro-Wilk parametric hypothesis test of composite normality, for sample size 3<= n <= 5000. Based on Royston R94 algorithm.
This test also performs the Shapiro-Francia normality test for platykurtic samples.
Cite As
Ahmed BenSaïda (2026). Shapiro-Wilk and Shapiro-Francia normality tests. (https://uk.mathworks.com/matlabcentral/fileexchange/13964-shapiro-wilk-and-shapiro-francia-normality-tests), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired: SimOutUtils, test, BoxPlotPro, Weighted Nonlinear Curve Fit Script with Plotter, Reference Interval Verification and Definition
General Information
- Version 1.1.0.0 (8.83 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.1.0.0 | - Improved precision for sample size = 3;
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| 1.0.0.0 | Change the value in line 136 to 0.26758 instead of 0.026758 (Shapiro-Francia) to correct the significance level. Thanks to Kent Parsons for his remarks. |
