Pearson Chi-squared Test
Pearson Chi-squared Test is a statistical test that measures the degree of association between two categorical variables. It is used to determine whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. The test is based on the assumption that the observed frequencies follow a multinomial distribution. The test statistic is calculated by summing the squared differences between the observed and expected frequencies, divided by the expected frequencies. The resulting statistic follows a chi-squared distribution with degrees of freedom equal to the number of categories minus one. The p-value obtained from the chi-squared distribution is used to determine the statistical significance of the test. A low p-value indicates that the observed frequencies are significantly different from the expected frequencies, while a high p-value indicates that there is no significant difference.
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