Final answer:
Chi-square analysis compares expected and observed values to test for significant differences, especially in genetics.
Explanation:
Chi-square analysis is primarily used to compare expected and observed values in a dataset. It tests the significance of the difference between observed and expected values by calculating a statistic that follows a chi-square distribution.
In genetics, chi-square tests help in assessing deviations from expected allele frequencies, aiding in determining if deviations are significant enough to reject the null hypothesis. The Chi-square test is utilized for various applications like analyzing counts in categorical data.
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