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Answer :
Final answer:
For a chi-square test, n (sample size) must be large enough so that for each cell of a contingency table, the expected cell count is 5 or more. Insufficient cell counts can lead to inaccurate inferences about the population.
Explanation:
In χ² testing, there is a rule of thumb to determine the validity of the application of this test statistic. This rule is referred to as the expected cell count requirement.
According to this rule, the correct condition that n (the sample size) must satisfy is: n must be large enough such that for each cell of a contingency table, the expected cell count is 5 or more. So the correct answer among the options provided will be C.
Insufficient expected cell counts can lead to a chi-square test producing an inaccurate inference about the population. This is because the chi-square test relies on approximation that becomes more accurate with larger expected cell counts.
Learn more about χ² testing here:
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