In a chi-squared goodness-of-fit test, if the expected frequencies $e _ { i }$ and the observed frequencies $f _ { i }$ were quite different, which of the following is the best conclusion? A) Null hypothesis is false, and reject Ho. B) Null hypothesis is true, and retain Ho. C) Alternative hypothesis is false, reject H_A. D) Chi-squared distribution is invalid, use t-distribution instead.

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Quizplus · Accepted Answer

In a chi-squared goodness-of-fit test, the null hypothesis is that the observed frequencies follow the expected frequencies. If the expected and observed frequencies are quite different, it suggests that the null hypothesis is not true and the researcher should reject it in favor of the alternative hypothesis. Therefore, the best conclusion would be to choose option A, which states that the null hypothesis is false and should be rejected. Option B can be eliminated as it opposes the given scenario. Option C is not a valid conclusion as it mentions the rejection of the alternative hypothesis, which is not how hypothesis testing works. Option D is also not correct as the chi-squared distribution is valid for such tests.

In a Chi-Squared Goodness-Of-Fit Test, If the Expected Frequencies eie _ { i }ei​

In a Chi-Squared Goodness-Of-Fit Test, If the Expected Frequencies $e _ { i }$