What are the consequences of violating the assumption of independence in a Chi-square test for goodness of fit?
- It can cause the test to be biased, leading to incorrect conclusions
- It can cause the test to be overly sensitive to small differences
- It can cause the test to have a lower power
- It can cause the test to incorrectly reject the null hypothesis
Violating the assumption of independence in a Chi-square test for goodness of fit can lead to biased results and incorrect conclusions. This is because the test assumes that the observations are independent, and this assumption is necessary for the test's validity.
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