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1. The single factor ANOVA tests for mean differences between 3 or more groups by comparing (Points : 1) Each population's variance. Each sample's variance.

1. The single factor ANOVA tests for mean differences between 3 or more groups by comparing (Points : 1) Each population's variance. Each sample's variance. Overall versus average sample variance. Overall versus average population variance. Question 2. 2. Excel's Two Factor ANOVA without Replication (Points : 1) provides a method to test multiple (>2) variables at the same time. provides a way to remove the influence of one variable on another variable. tests for interaction impact among the factors being tested. requires a large p-value to reject all of the tested hypothesis statements. Question 3. 3. Eta squared is calculated the same way for all effect size measures in the various ANOVA versions; MS Error/MS Total. (Points : 1) True False. Question 4. 4. What is the best reason to perform an ANOVA test rather than multiple t-tests? (Points : 1) to ensure the overall confidence level remains the same. It is easier to perform one test than several tests. This depends upon the individual preference of the researcher. We shouldn't - multiple t-tests are more precise. Question 5. 5. The mean difference calculation involves using (Points : 1) MS within MS Between SS Within SS Between Question 6. 6. The single factor ANOVA mean difference calculation involves (Points : 1) paired mean differences. a t-value. a variation estimate. all of the above. Question 7. 7. The E in a significance of F value means (Points : 1) Exponent Error Expand None of the above Question 8. 8. What question does the ANOVA test answer? (Points : 1) Do all means differ? Does one mean equal another? Are all means equal? Are all variances equal? Question 9. 9. The effect size measure for the single factor ANVOA is called eta squared and equals the SS Between/SS Total. (Points : 1) True False Question 10. 10. ANOVA's SS within is an estimate of the overall variance in the data set. (Points : 1) True False

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