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“The Chi-square test of homogeneity is a common statistical test used to determine whether a sample data sets or data set (observations) are drawn from a homogeneous population. This is because many tests in statistics focus on the homogeneity of the population, so Chi-square tests of homogeneity are an important tool in many research studies. The test determines whether the observed sample data sets are generated from a single population. The population under study is called the “null” population and is often assumed to be a random sample of a large population, whereas the observed samples
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The Chi-square test of homogeneity provides an analytical technique to evaluate the homogeneity of the variance of categorical data. In other words, it determines whether the differences between the means (µa and µb) and the variances (σa and σb) of two categories are due to the same underlying population parameter. In other words, Chi-square is used to compare the differences between two categories, based on the differences in means and variances. It is widely used in statistics and has practical significance in applications,
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