Practice of Nursing Research Appraisal Synthesis 7th Edition By Grove Burns
Practice of Nursing Research Appraisal Synthesis 7th Edition By Grove Burns
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Chapter 25: Using Statistics to Determine Differences
Complete Chapter Questions With Answers
Sample Questions Are Posted Below
MULTIPLE CHOICE
| a. | Whether one variable seems related to another one |
| b. | Whether two variables cause one another |
| c. | Whether an intervention changes the dependent variable’s value |
| d. | Change over time |
ANS: A
The chi-square (c²) test compares differences in proportions of nominal level variables. A two-way chi-square is a statistic that tests whether proportions in levels of one variable are significantly different from proportions of the second variable. In other words, it detects whether one nominal variable seems to be related to another one.
DIF: Cognitive Level: Analysis REF: Page 587
| a. | The effect that the interventional conditions produce |
| b. | The average of all variations in the data set |
| c. | Total variation |
| d. | The differences that exist among the several interventional conditions |
ANS: A
The term “mean square” (MS) is used interchangeably with the word “variance.” The formulas for ANOVA compute two estimates of variance: the between groups variance and the within groups variance. The between groups variance represents differences between the groups/conditions being compared, and the within groups variance represents differences among (within) each groups’ data. Therefore, the formula is F = MS between/MS within.
DIF: Cognitive Level: Analysis REF: Page 585
| a. | Mann-Whitney U |
| b. | Chi-square |
| c. | ANOVA |
| d. | t-test |
ANS: D
One of the most common parametric analyses used to test for significant differences between group means of two samples is the t-test. In its calculation, the numerator is the difference scores of the means of the two samples. In addition, the test uses the pooled standard deviation of the two samples as the denominator.
DIF: Cognitive Level: Comprehension REF: Page 580
| a. | A researcher is reluctant to perform a post hoc analysis that would require a more stringent level of significance. |
| b. | The F-statistic would be invalidated by the second test. |
| c. | If hypothesis testing reveals that a difference between groups exists, it is obvious what two groups those are. |
| d. | Sample sizes are not large enough for this analysis. |
ANS: C
Post hoc tests have been developed specifically to determine the location of group differences after ANOVA is performed on data from more than two groups. The post-hoc analyses performed after the ANOVA preserves the same level of analysis as the ANOVA itself. The F-statistic is not invalidated by performing a post hoc analysis. Sample size is not a consideration when performing a post hoc analysis.
DIF: Cognitive Level: Analysis REF: Page 586
| a. | It is almost always statistically significant. |
| b. | It is used for two nominal variables |
| c. | It demands normal distribution, even of dichotomous variables. |
| d. | It is parametric. |
ANS: B
The chi-square (c²) test compares differences in proportions of nominal level variables. Statistical significance may or may not exist. The test does not demand normal distribution, and it is non-parametric.
DIF: Cognitive Level: Analysis REF: Page 587
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