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Test goodness of fit and analyze categorical data distributions
Karl Pearson developed the chi-square test to analyze categorical data distributions.
Tests whether observed frequencies match expected theoretical distributions.
Widely used in clinical trials to compare treatment outcomes across groups.
Mendel could have used it to validate his pea plant inheritance patterns.
Companies use chi-square to analyze customer preferences and survey responses.
Manufacturing uses it to detect defects and ensure product consistency.
Pollsters use chi-square to verify if voting patterns match predictions.
Tech companies rely on it to determine if website changes improve conversions.
The chi-square test compares observed frequencies with expected frequencies to determine if there is a significant difference. It is commonly used in hypothesis testing for categorical data, quality control, and scientific research.