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Martin, Physicist

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What is the advantage of a one-tailed test over a two-tailed

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What is the advantage of a one-tailed test over a two-tailed test? (Points : 1) Less data variability in the groups involved. Smaller critical values indicate significance. Rejecting at HO = .05 involves less chance of error. There are fewer calculations to make.

2. What is the probability of type II error when the null hypothesis is rejected? (Points : 1) 0.5 0.05 0.025 0

3. Why do the critical values change with degrees of freedom for the t-tests? (Points : 1) Different degrees of freedom define different t distributions. Because the critical values are calculated directly from degrees of freedom. The degrees of freedom reflect the value of SEM. The degrees of freedom are indexed to the M – μM difference.

4. The one-sample t-test differs from the z-test in which way? (Points : 1) There are no parameter values involved in a t-test. The t-test is more sensitive to minor differences between sample and population. With the t-test one can be confident of the normality of the data. The t-test requires no parameter standard error of the mean.

5. Which is the symbol used for the test statistic in ANOVA? (Points : 1) M z t F

6. To what does “main effect” refer in an ANOVA of company sales? (Points : 1) It means the “primary influence”. It refers to the sum of the error variance. It designates the interaction of variables. It refers to an independent variable.

7. What statistic measures data variability in both groups in an independent t-test? (Points : 1) The critical value of t. The M1 – M2 difference. The calculated value of t. The SEd.

8. When a significant interaction is graphed, what is indicated on the vertical axis? (Points : 1) The dependent variable. The complexity of the interaction. The independent variable. The error term.

9. Theoretically, how many independent variables can a factorial ANOVA accommodate? (Points : 1) 1 2 4 any number

10. How do statistical tests like the one sample t adjust for the absence of parameter values? (Points : 1) The values are estimated from sample data. The values are assumed to have a constant value. The test is reconstructed so that the values aren’t needed. The test is reformulated so that data are always normal.

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