MATLAB-Based Implementation for Chi-Square Goodness-of-Fit Test Algorithm
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Developed on the MATLAB platform, this program serves as a computational tool for implementing the chi-square goodness-of-fit test algorithm. The primary application of this algorithm is to detect deviations and errors between observed values and theoretical expectations, thereby evaluating how well a given data distribution fits a specified theoretical model. The implementation leverages MATLAB's built-in statistical functions, such as chi2gof, and allows users to customize significance levels, binning strategies, and distribution parameters. Key features include automated calculation of test statistics, degree-of-freedom adjustments, and p-value generation for hypothesis testing. By modifying algorithmic parameters or integrating alternative distribution models, users can further enhance the test's accuracy and computational efficiency. The program also supports batch processing for large datasets and visualization of fitted distributions versus empirical data.
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