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In quantitative research, statistical tests like Chi-square, t-test, and F-test are widely used to analyze data and make inferences about populations. Each of these tests has distinct features and applications, making them essential tools in experimental and survey-based research. The Chi-square test is primarily used to examine the association between categorical variables. Its most notable feature is that it deals with frequencies or counts rather than measurements on a continuous scale. This test is non-parametric, meaning it does not assume a specific distribution for the data, making it flexible for analyzing nominal or ordinal data. The test evaluates whether the observed frequencies differ significantly from the expected frequencies under the null hypothesis of independence. Chi-square is commonly applied in contingency tables, goodness-of-fit tests, and tests of homogeneity. Another important feature is __________ _____ _____ _____ ___ ______ ________ _______.
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