1. Point estimates provide less confidence in indicating a parameter’s value than a confidence interval.

True

False

2. Confidence intervals provide an indication of how much variation exists in the data set.

True

False

3. The probability that the actual population mean will be outside of a 98% confidence interval is

1%

2%

4%

5%

4. The Chi-square test measures differences in frequency counts rather than differences in size (such as the t-test and ANOVA).

True

False

5. Chi-square tests are more likely to have type II (falsely rejecting the null hypothesis) errors than parametric tests.

True

False

6. A contingency table is a multiple row and multiple column table showing counts in each cell.

True

False

7. For a one sample confidence interval, the interval is calculated around the estimated population mean or standard (?m ).

True

False

8. In confidence intervals, the width of the interval depends only on the variation within the data set.

True

False

9. 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.

True

False

10. The Chi-square test is very sensitive to small differences in frequency differences.

True

False