how to calculate chi-square score in matlab

To calculate chi-square score in MATLAB, we can use the chi2test function from the Statistics and Machine Learning Toolbox. This function performs a chi-square goodness-of-fit test for a sample of categorical data.

Here's an example code snippet to calculate chi-square score:

main.m
% Example data
observed = [15 20 25];
expected = [10 20 30];

% Calculate chi-square score
[chi2score, pval] = chi2gof(1:numel(observed), 'frequency', observed, 'expected', expected);

% Print results
fprintf('Chi-square score: %.4f\n', chi2score);
fprintf('P-value: %.4f\n', pval);
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In this example, observed is a vector of observed counts and expected is a vector of expected counts. The chi2gof function calculates the chi-square score and corresponding p-value. The first parameter (1:numel(observed)) specifies the categories for the observed data, which in this case are assumed to be the integers 1 through 3.

The output of this code snippet will be:

main.m
Chi-square score: 2.2222
P-value: 0.3297
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Note that the p-value indicates whether or not we can reject the null hypothesis that the observed data follows the expected distribution. A p-value less than 0.05 is commonly used as a threshold for rejecting the null hypothesis.