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1. Question : The goodness of fit test null hypothesis states that the sample data does not match an expected distribution. Question 2. Question : Statistical significance in the Chisquare test means the population distribution (expected) is not the source of the sample (observed) data. Question 3. Question : While rejecting the null hypothesis for the goodness of fit test means distributions differ, rejecting the null for the test of independence means the variables interact. Question 4. Question : The null hypothesis for the test of independence states that no correlation exists between the variables. Question 5. Question : For a one sample confidence interval, the interval is calculated around the calculated sample mean (m). Question 6. Question : For a one sample confidence interval, if the interval contains the Îźm , the corresponding t-test will have a statistically significant result â€“ rejecting the null hypothesis. Question 7. Question : The distribution for the goodness of fit test equals k-1, where k equals the number of categories. Question 8. Question : Chi-square tests rarely have type I errors. Question 9. Question : Confidence intervals provide an indication of how much variation exists in the data set. Question 10. Question : The Chi-square test is very sensitive to small differences in frequency differences.

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