Chi-squared Test
Chi-squared test is a statistical hypothesis test that determines whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. It is used to analyze categorical data and is commonly used in fields such as genetics, marketing research, and social sciences. The test involves calculating the difference between the observed and expected frequencies, squaring the difference, dividing by the expected frequency, and summing across all categories. The resulting statistic follows a chi-squared distribution, and the p-value is used to determine the significance of the difference. A low p-value indicates that the observed frequencies are significantly different from the expected frequencies, while a high p-value indicates that the observed frequencies are not significantly different from the expected frequencies.
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