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Data Analysis Using SQL and Excel - Second Edition
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The chi-square test (pronounced to rhyme with “guy” and starting with a hard “c” sound) provides another method for addressing the question “how different is different?” The chi-square test is appropriate when comparing multiple dimensions to each other. Instead of just looking at the “stop rate” for customers, for instance, the customers are divided into two distinct groups, those who stopped and those who are active. These groups can then be compared across different dimensions, such as channel, market, or the period when they started.
The chi-square test does not create confidence intervals because confidence intervals do not make as much sense across multiple dimensions. Instead, it calculates the confidence that the observed counts are due to chance by comparing the observed counts to expected counts. Because the chi-square test does not use confidence intervals, it avoids some of the logical conundrums that occur...
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