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The Normal Distribution Analyser function offers automatic visual insights through histograms and Q-Q plots, and also provides essential statistical measures like skewness and kurtosis. It evaluates your data against renowned statistical tests including Shapiro-Wilk, Kolmogorov-Smirnov, Anderson-Darling, Jarque-Bera, and Lilliefors tests. The function compiles resulting P-values in a concise table, allowing you to determine whether your data follows a normal distribution accurately. It enhances your data analysis with this indispensable utility, ensuring robust statistical assessments.
Key Features:
- Automatic detection of Normal Distribution data
- Histogram and Q-Q plot visualization
- Skewness and kurtosis assessment
- Shapiro-Wilk, Kolmogorov-Smirnov, Anderson-Darling, Jarque-Bera, and Lilliefors tests
- Tabulated output of P-values for easy interpretation
- Precise evaluation of data normality
Cite As
ASWIN SEKHAR C S (2026). Normal Distribution Analyser (https://au.mathworks.com/matlabcentral/fileexchange/134032-normal-distribution-analyser), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.1 (4.12 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
