## Understanding Nursing Research 5th Edition Burns Grove Test Bank

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# Understanding Nursing Research 5th Edition Burns Grove Test Bank

ISBN-13: 978-1437707502

ISBN-10: 1437707505

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# Understanding Nursing Research 5th Edition Burns Grove Test Bank

ISBN-13: 978-1437707502

ISBN-10: 1437707505

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# Free Nursing Test Questions:

**Burns: Understanding Nursing Research, 5 ^{th} Edition**

** **

**Chapter 11: Understanding Statistics in Research**

** **

**Test Bank**

** **

**MULTIPLE CHOICE**

- What proportion of the standardized scores of a sample lies between the Z-scores of –1.96 and +1.96?

a. | 34.0% |

b. | 47.7% |

c. | 68.3% |

d. | 95.5% |

ANS: D

Z-scores are a common standardized score used to express deviations from the mean in terms of standard deviation units. Figure 12-1 demonstrates that standardized scores lying between the Z-score of –1.96 and +1.96 are distributed over 95.5% of the normal curve.

34.0% of cases will be 1 score above or below the mean.

Approximately 47.7% of cases will be 1.96 above OR below the mean.

68.3% of cases will lie between the Z-scores of –1.0 and +1.0.

DIF: Cognitive level: Synthesis REF: p. 388

- Descriptive statistics should be reported in every study to:

a. | determine validity. |

b. | indicate reliability. |

c. | provide a powerful analysis of data. |

d. | show the sample characteristics. |

ANS: D

The researcher needs to obtain as complete a picture of the sample as possible.

Frequencies of descriptive variables related to the sample are usually obtained first.

Validity is not determined by descriptive statistics.

Descriptive statistics would not indicate reliability.

Descriptive statistics are not “powerful analysis” measures.

DIF: Cognitive level: Comprehension REF: p. 383

- A researcher notes that 3 of 30 subjects had extreme anxiety scores when compared with the other subjects. These three subjects would be treated as:

a. | deviants. |

b. | outliers. |

c. | unexpected findings. |

d. | ungrouped participants. |

ANS: B

Subjects with extreme values that seem unlike the rest of the sample are called outliers.

Deviants and outliers are not the same.

Unexpected findings can occur with or without outliers.

Subjects can be grouped into categories or not, the process may highlight outliers, but would not define them.

DIF: Cognitive level: Application REF: p. 374

- Results of an ANOVA analysis of three specialty nursing groups indicate there is a significant difference between groups on the practice of spiritual care. To determine where the difference occurs, the researcher would need to run which statistical analyses?

a. | Confirmatory |

b. | Post hoc |

c. | Predictive |

d. | Relational |

ANS: B

Some statistical analyses, such as chi-square and analyses of variance (ANOVA), are used to test for differences among groups in studies including more than two groups. These tests do not indicate which groups are different. Post hoc analyses are used to identify the specific groups that are different.

Confirmatory analysis is performed to confirm expectations regarding the data.

Predictive research seeks to forecast situations in the future based on current knowledge.

Relational analysis determines a connection between the variables.

DIF: Cognitive level: Application REF: p. 375

- The likelihood that a statistical value obtained through analysis of the data is likely to occur in any two samples selected from the same population is called:

a. | degrees of freedom. |

b. | induction. |

c. | interval estimation. |

d. | probability. |

ANS: D

Probability is used to explain the extent of a relationship, the probability of an event occurring in a given situation, or the probability of accurately predicting an event.

Degrees of freedom is the freedom of a score’s value to vary given the existing situation.

Induction is a type of reasoning.

Interval estimation is the researcher’s best guess as to the range of scores for the study population.

DIF: Cognitive level: Analysis REF: p. 376

- The level of significance usually set in nursing studies is at either:

a. | .5 or .1. |

b. | .03 or .003. |

c. | .05 or .01. |

d. | .005 or .001. |

ANS: C

The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.

.5 or .1 values are too high. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.

.03 or .003 values are not generally accepted levels of significance. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.

.005 or .001 values would be too rigorous. The level of significance selected for most nursing studies is .05. In some studies, the more rigorous level of significance of .01 may be chosen.

DIF: Cognitive level: Knowledge REF: p. 377

- A researcher reports that results of a study were not statistically significant. How is this to be interpreted?

a. | Intervention was not strong enough to make a difference. |

b. | Researcher does not have enough evidence to reject the null hypothesis. |

c. | Researcher’s logic or conceptualization in setting up the study was faulty. |

d. | Topic is of no further interest to nurse researchers or clinicians. |

ANS: B

If the results of the study are not statistically significant, the researcher was unable to show there was a mathematical difference between the groups. The null hypothesis, which states there is no difference between groups, would therefore be supported. The null hypothesis cannot be rejected in this case.

Although it may be true that the intervention was not strong enough to make a difference, it does not relate to the statistical significance.

It may be true that the researcher’s logic or conceptualization in setting up the study was faulty, but cannot be read into the statement regarding statistical significance.

The topic may still be a very worthwhile area of study. The lack of statistically significant results does not mean that the topic is not a clinically significant topic.

DIF: Cognitive level: Synthesis REF: p. 377

- A statistically significant finding means that:

a. | findings are clinically important and valuable. |

b. | interventions should be used in clinical practice. |

c. | obtained results are not likely to have been due to chance. |

d. | results will be the same if the study is repeated with another sample. |

ANS: C

Statistical significance indicates the likelihood that results of a statistical analysis are real and not a result of chance. The calculated probability from the statistical analysis is compared with alpha to determine whether findings are statistically (mathematically) significant or not.

Statistical significance does not necessarily mean clinically significant. Statistical significance indicates the likelihood that results of a statistical analysis are real and not a result of chance.

Clinicians must evaluate findings for relevance to their own practice.

There is no guarantee that results will be the same from one study to the next, especially if it is early in the exploration of the topic.

DIF: Cognitive level: Synthesis REF: p. 377

- Which of the following is true about the level of significance? The level of significance:

a. | ensures that findings will be correct 95% of the time if an alpha value of less than 0.05 is used. |

b. | refers to a statistic calculated during computer analysis of data. |

c. | represents the probability of getting a calculated statistic as high as the one found in the study if the null hypothesis is really true. |

d. | represents the risk the researcher is willing to take in making a Type I error and is established before data are analyzed. |

ANS: D

A Type I error occurs when the null hypothesis is rejected, though it is actually true. The level of significance is the cutoff point selected by the researcher before data collection that indicates the probability of a true significant difference between groups.

It is the likelihood of correct findings, but cannot ensure that they actually are correct.

A “p value” is calculated by the computer, but this is compared to the level of significance determined acceptable by the researcher.

It actually has to do with making a Type I error. A Type I error occurs when the null hypothesis is rejected, though it is actually true.

DIF: Cognitive level: Synthesis REF: p. 377

- Which of the following questions relates to generalization?

a. | Are the findings generally significant to people in the study? |

b. | Can these findings be applied to other groups or settings? |

c. | Does the degree of control in the study allow for statistical significance? |

d. | How many alternative explanations or rival hypotheses can be proposed? |

ANS: B

Generalization is the application of information to a general situation (in this case other groups or settings) that has been acquired from a specific instance (research study).

The issue of significance is determined differently than generalizability.

Control relates to the research methodology.

This question has to do with controls involved in the study and the methodology that was used.

DIF: Cognitive level: Analysis REF: p. 378

- Which of the following interpretations is acceptable as worded?

a. | Findings suggest that cholesterol levels influence cardiac blood flow. |

b. | Results demonstrate that lithium has hazardous side effects in all humans. |

c. | The positive correlation between age and reaction time indicates that age is a causal factor in automobile accidents. |

d. | The study proved that cigarette smoking causes lung cancer. |

ANS: A

Researchers can never prove things using inferential reasoning; they can never be certain their reasoning is correct. Correlations do not indicate causality; they simply express a relationship. Because of the limitations of research and the diversity of humans, the ability to generalize findings to “all” members of a population is not possible.

Findings can never be applied to all humans.

Correlation does not equate with causation.

The study cannot prove that something is the case; it can only support the likelihood.

DIF: Cognitive level: Analysis REF: p. 375

- There is a greater risk of making which error with a directional hypothesis?

a. | Concluding that there is a difference between groups when there really is no difference |

b. | Concluding that there is no difference between groups when there is an inverse relationship |

c. | Concluding that there is no difference between groups when there really is a difference |

d. | Rejecting the null hypothesis when the measurement error is moderate |

ANS: A

In a one-tailed test of significance, the hypothesis is directional. One-tailed statistical tests are uniformly more powerful than two-tailed tests, decreasing the possibility of a Type II error (saying there is no difference when there really is). This means the likelihood of a Type I error (saying there is a difference when there really is not) increases.

Concluding that there is no difference between groups when there is an inverse relationship is a Type II error.

Concluding that there is no difference between groups when there is an inverse relationship describes a Type II error.

Rejecting the null hypothesis when the measurement error is moderate would be true of both directional and nondirectional hypotheses.

DIF: Cognitive level: Analysis REF: p. 381

- Which of the following is true about Type I errors?

a. | Considered only when results are not statistically significant in a study |

b. | Extremely likely to happen when p is less than 0.001 |

c. | More likely to happen when p is less than 0.01 rather than p is less than 0.05 |

d. | Occur when the researcher says there is a significance, but findings are actually not statistically significant |

ANS: D

With a Type I error, study results indicate there is a significant difference, when in reality there is not.

Researchers should always be concerned with both Type I and Type II errors. With a Type I error, study results indicate there is a significant difference, when in reality there is not.

A Type I error is less likely to happen with smaller and smaller levels of significance. With a Type I error, study results indicate there is a significant difference, when in reality there is not. C. With a Type I error, study results indicate there is a significant difference, when in reality there is not.

DIF: Cognitive level: Knowledge REF: p. 381

- Level of significance, sample size, power, and effect size are the four components of:

a. | decision theory. |

b. | exploratory analysis. |

c. | inference. |

d. | power analysis. |

ANS: D

Cohen identified four parameters of a power analysis: the level of significance, sample size, power, and effect size.

The four components do not constitute decision theory.

Exploratory analysis is a preliminary step in the analysis of data.

Inference is the conclusion or judgment based on evidence.

DIF: Cognitive level: Knowledge REF: p. 382

- A Type I error could occur for which of the following reasons?

a. | Large difference between groups |

b. | Large sample size |

c. | Lenient level of significance |

d. | Normal distribution |

ANS: C

There is a greater risk of Type I error with a 0.05 level of significance than with a 0.01 level of significance. As the level of significance becomes more extreme, the risk of a Type I error decreases.

The greater the difference between groups the less likelihood of a Type I error.

A Type I error is probably less likely with a large sample.

Normal distribution is not going to cause a Type I error.

DIF: Cognitive level: Analysis REF: p. 381

- Which of the following levels of significance would decrease the chance of a Type II error?

a. | 0.10 |

b. | 0.05 |

c. | 0.01 |

d. | 0.001 |

ANS: A

There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.

There would be less chance of a Type II error with 0.05 than with 0.01 or 0.001, but 0.10 is even more liberal. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.

There would be less chance of a Type II error with 0.01 than with 0.001, but 0.10 is even more liberal. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.

This is the most restrictive answer and therefore the greatest risk of a Type II error. There is a greater risk of Type II error with more extreme levels of significance and less of a risk with more conservative levels of significance.

DIF: Cognitive level: Knowledge REF: p. 382

- Type I errors are more likely to occur when the level of significance is less than:

a. | 0.05. |

b. | 0.01. |

c. | 0.001. |

d. | 0.0001. |

ANS: A

There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.

There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.

This level of significance is more extreme than 0.01. There is a greater risk of a Type I error with a .05 level of significance than with a 0.01 level of significance.

There is a greater risk of a Type I error with a 0.05 level of significance than with a 0.01 level of significance.

DIF: Cognitive level: Knowledge REF: p. 381

- Under what condition would the mean, median, and mode be equal?

a. | Equal range and standard deviation |

b. | Multimodal distribution of scores |

c. | Normal distribution of scores |

d. | Small variance |

ANS: C

In the normal curve, the mode, median, and mean are equal.

Equal range and standard deviation would not mean that the mode, median, and mean are equal. In the normal curve, the mode, median, and mean are equal.

With a multimodal distribution, the mean, median, and mode would not be equal. In the

normal curve, the mode, median, and mean are equal.

A small variance would not mean that the mode, median, and mean are equal. In the normal curve, the mode, median, and mean are equal.

DIF: Cognitive level: Analysis REF: p. 379

- In the following frequency distribution of data, the score 12 is which measure of central tendency?

X |
f |

12 | 3 |

11 | 0 |

10 | 1 |

9 | 1 |

8 | 1 |

7 | 1 |

a. | Frequency |

b. | Mean |

c. | Median |

d. | Mode |

ANS: D

The mode is the numerical value or score that occurs with greatest frequency. In this example, the score 12 occurs three times in the data set.

Frequency is how many times a certain score is recorded in the data. The mode is the numerical value or score that occurs with greatest frequency.

The mean is the sum of the scores divided by the number of scores being summed. The mode is the numerical value or score that occurs with greatest frequency.

The median is the score at the exact center of the ungrouped frequency distribution. The mode is the numerical value or score that occurs with greatest frequency.

DIF: Cognitive level: Analysis REF: p. 385

- The mean is represented by which score in the following frequency distribution?

X |
f |

12 | 3 |

11 | 0 |

10 | 1 |

9 | 1 |

8 | 1 |

7 | 1 |

** **

** **

a. | 12 |

b. | 10 |

c. | 9 |

d. | 7 |

ANS: B

The mean is the sum of the scores divided by the number of scores being summed. In this example, the sum of scores equals 70, and the number of scores being summed equals 7. Seventy divided by 7 equals 10.

DIF: Cognitive level: Analysis REF: p. 387

- The median is represented by which score in the following frequency distribution?

X |
f |

12 | 3 |

11 | 0 |

10 | 1 |

9 | 1 |

8 | 1 |

7 | 1 |

a. | 12 |

b. | 10 |

c. | 9 |

d. | 7 |

ANS: B

The median is the score at the exact center of the frequency distribution (the 50th percentile). The median is obtained by first rank ordering the scores, then identifying the score at the exact center. In this example, rank ordering of the scores would be: 7, 8, 9, 10, 12, 12, 12. 10 is the center score.

Twelve is the mode. The median is the score at the exact center of the frequency distribution (the 50th percentile). The median is obtained by first rank ordering the scores, then identifying the score at the exact center.

The median is the score at the exact center of the frequency distribution (the 50th percentile). The median is obtained by first rank ordering the scores, then identifying the score at the exact center.

The median is the score at the exact center of the frequency distribution (the 50th percentile). The median is obtained by first rank ordering the scores, then identifying the score at the exact center.

DIF: Cognitive level: Analysis REF: pp. 385-387

- In estimating the parameters of a population of students categorized by year in school, which of the following estimators is the most nonbiased?

a. | Mean |

b. | Median |

c. | Standard deviation |

d. | Variance |

ANS: B

Categories of year in school (freshmanRemember,phomore, junior, and senior) indicate ordinal data. The median is the most appropriate measure of central tendency for ordinal data.

Year in school is ordinal data; a mean cannot be calculated on ordinal data. Categories of year in school (freshmanRemember,phomore, junior, and senior) indicate ordinal data. The median is the most appropriate measure of central tendency for ordinal data.

Standard deviation requires at least interval level data for calculation. Categories of year in school (freshmanRemember,phomore, junior, and senior) indicate ordinal data. The median is the most appropriate measure of central tendency for ordinal data.

Variance requires at least interval level data for calculation. Categories of year in school (freshmanRemember,phomore, junior, and senior) indicate ordinal data. The median is the most appropriate measure of central tendency for ordinal data.

DIF: Cognitive level: Analysis REF: p. 387

- What percent of scores will be within one standard deviation above or below the mean?

a. | 34 |

b. | 68 |

c. | 95 |

d. | 99 |

ANS: B

In the normal curve, 68% of the scores will be within one standard deviation above or below the mean.

DIF: Cognitive level: Knowledge REF: p. 388

- Which of the following measures would be helpful in interpreting the relationship of a particular score to the distribution?

a. | Frequency |

b. | Mean |

c. | Standard deviation |

d. | Variance |

ANS: C

The standard deviation indicates the average deviation of a score from the mean in that particular sample.

The frequency tells how many times a score occurs in the distribution, not where it falls. The standard deviation indicates the average deviation of a score from the mean in that particular sample.

The mean is simply the average of the scores and would not indicate a relationship to the distribution of scores. The standard deviation indicates the average deviation of a score from the mean in that particular sample.

Variance is a calculated value and has no absolute value. The standard deviation indicates the average deviation of a score from the mean in that particular sample.

DIF: Cognitive level: Application REF: p. 388

- Standard deviation is defined as:

a. | a difference score based on the lowest and highest value in the set. |

b. | scores grouped so that the range in each set is standardized and equal. |

c. | scores that have been standardized to have a mean of zero. |

d. | the average difference between the mean and each of the scores in the set. |

ANS: D

Scores that have been standardized to have a mean of zero describes a Z-score.

The difference between the lowest and highest values in the set is a definition of the range of the data.

The standard deviation indicates the average deviation of a score from the mean in that particular sample. Just as the mean is the average score, the standard deviation is the average difference score.

Scores grouped so that the range in each set is standardized and equal refers to grouped frequency distributions.

DIF: Cognitive level: Application REF: p. 388

- The mean scores of two groups participating in a study are exactly the same for a particular variable. This suggests that the:

a. | average score is the same, but distribution of scores for each group are not known. |

b. | distribution and range of scores will be similar. |

c. | groups are definitely heterogeneous in relation to this variable. |

d. | groups are very much alike in relation to the variable. |

ANS: A

The mean is a measure of central tendency and indicates the average score of a group, but does not indicate the variability of the scores around the mean. A measure of dispersion is required to demonstrate the distribution of scores.

Because the mean is the same on one variable does not mean that the two groups are the same in other ways.

If groups are definitely heterogeneous in relation to this variable, this would mean that the groups are very different.

The exact same mean does not equate to sameness in other ways.

DIF: Cognitive level: Application REF: p. 387

- Assuming a normal distribution, where would you find approximately two thirds of the scores if they ranged from 30 to 68, M = 45, and SD = 7? Between:

a. | 30 and 68 |

b. | 31 and 59 |

c. | 37 and 61 |

d. | 38 and 52 |

ANS: D

In the normal curve, 68% of scores will be within one standard deviation above or below the mean. In the example, two thirds of scores (66%) fall between 30 and 68. The mean = 45 and the SD = 7 for this sample. It follows that scores will fall between one standard deviation below (45 – 7 = 38) and one standard deviation above the mean (45 + 7 = 52).

DIF: Cognitive level: Application REF: p. 388

- Which of the following will be most affected by scores that are extremely high or extremely low?

a. | Mean |

b. | Median |

c. | Mode |

d. | All of the above are affected equally. |

ANS: A

The mode and median are not affected by outliers as is the mean.

DIF: Cognitive level: Application REF: pp. 385-387

- The mean of the following set of numbers (12, 4, 13, 20, 4, 10, 14) is:

a. | 4. |

b. | 10. |

c. | 11. |

d. | 17. |

ANS: C

The mean refers to the sum of the scores divided by the number of scores being summed. The sum of scores in this example equals 77. Seventy-seven divided by 7, the number of scores, equals 11.

Four occurs most often in the list and is therefore the mode.

Ten is an incorrect answer. The mean refers to the sum of the scores divided by the number of scores being summed.

Seventeen is an incorrect answer. The mean refers to the sum of the scores divided by the number of scores being summed.

DIF: Cognitive level: Application REF: p. 387

- The median of the following set of numbers (12, 4, 13, 20, 4, 10, 14) is:

a. | 4. |

b. | 11. |

c. | 12. |

d. | 17. |

ANS: C

The median is the score at the exact center of the frequency distribution after scores are placed in rank order. In the example, the rank order of scores is (4, 4, 10, 12, 13, 14, 20). The score at the exact center of the distribution, then, is 12.

Four occurs most often in the list and is therefore the mode.

Eleven is the mean of the distribution. The median is the score at the exact center of the frequency distribution after scores are placed in rank order.

Seventeen is an incorrect answer. The median is the score at the exact center of the frequency distribution after scores are placed in rank order

DIF: Cognitive level: Application REF: pp. 385-387

- Which of the following is an exploratory data analysis technique that is used to graphically illustrate the relationship of scores on one variable with scores on another variable?

a. | Box-and-whiskers plot |

b. | Q-plot |

c. | Scatterplot |

d. | Stem-and-leaf display |

ANS: C

Scatterplots can be used to illustrate the relationship of scores on one variable with scores on another.

The box-and-whiskers plot is used for exploratory data analysis.

The Q-plot is an exploratory data analysis technique that displays the scores or data in a distribution by quantile.

A stem-and-leaf display presents scores visually to obtain insight.

DIF: Cognitive level: Knowledge REF: p. 389

- Which test statistic is calculated for Pearson product moment correlation?

a. | F |

b. | r |

c. | t |

d. | C^{2} |

ANS: B

The Pearson product moment correlation is represented by the “r” correlation coefficient statistic

The F statistic is a calculated value that determines significance in data analysis.

The *t* test uses the standard deviation of the sample to estimate the standard error of the sampling distribution.

X^{2} is the symbol for the Chi-square statistic.

DIF: Cognitive level: Knowledge REF: pp. 394-395

- Which of the following is true about the chi-square statistic?

a. | Expected and observed frequencies or proportions are compared. |

b. | Interval level data are used for all variables. |

c. | Post hoc testing is used to identify areas of group differences. |

d. | Results are reported in terms of differences between group means. |

ANS: A

The chi-square test of independence examines the frequencies of observed data and compares

them with the frequencies that could be expected to occur if the data categories were actually independent of each other.

The data do not have to be interval level.

Post hoc analyses can be used to identify the categories where the differences lie.

Results are reported as differences from expected frequencies.

DIF: Cognitive level: Knowledge REF: p. 401

- Which of the following is true about the Pearson product moment correlation?

a. | Determines relationships between a set of predictors and one outcome |

b. | Examines bidirectional relationships between two variables |

c. | Investigates relationships between an independent and dependent variable |

d. | Measures variables at the nominal level |

ANS: B

Correlational analyses are performed to identify relationships between or among variables. Variables can vary (change in different directions) or change in the same direction.

The Pearson product moment correlation does not determine relationships between a set of predictors and one outcome. Correlational analyses are performed to identify relationships between or among variables. Variables can vary (change in different directions) or change in the same direction.

It measures the extent of relationship between two variables or among variables. Correlational analyses are performed to identify relationships between or among variables. Variables can vary (change in different directions) or change in the same direction.

Data do not need to be nominal level for this statistic. Correlational analyses are performed to identify relationships between or among variables. Variables can vary (change in different directions) or change in the same direction.

DIF: Cognitive level: Application REF: pp. 394-395

- If a nurse researcher found that older patients asked fewer questions before surgery than younger patients, the relationship would be described statistically as:

a. | negative. |

b. | null. |

c. | positive. |

d. | random. |

ANS: A

In a negative relationship, a high score on one variable is related to a low score on the other variable. In this example, the older the person, the fewer questions they asked and the younger the patient, the more questions they asked. The relationship goes in different directions. As one relationship goes down (older age and fewer questions), the other goes up (younger age and more questions).

Null means that there is no difference.

Positive relationships mean that as the score on one variable goes up, the score on the other variable goes up also.

A random relationship would imply a low or near-zero correlation.

DIF: Cognitive level: Analysis REF: p. 395

- Which of the following correlation coefficients shows the strongest relationship?

a. | 0.10 |

b. | 0.30 |

c. | 0.90 |

d. | 0.92 |

ANS: D

As the negative or positive values approach zero, the strength of the relationship decreases. As the *r* value approaches –1 or +1, the strength of the relationship increases.

DIF: Cognitive level: Analysis REF: p. 395

- What statistical test would you use to test the difference in heart rate response to exercise between a group of cardiac patients involved in a formal cardiac rehabilitation program and another group exercising at home?

a. | Central tendency |

b. | Chi-square |

c. | Pearson product moment correlation |

d. | t-test |

ANS: D

The *t*-test is used to determine if there is a significant difference between groups with data measured at the interval or ratio level.

There are several measures of central tendency; none of them would be used to find a significant difference between groups.

Chi-square determines whether two variables are independent or related.

Pearson product moment correlation is a parametric test used to determine relationships among variables.

DIF: Cognitive level: Analysis REF: p. 404

- The information, “t = 9.28 (df = 18)” indicates:

a. | that it is unlikely there is a significant difference in scores between groups. |

b. | that more than two groups of subjects participated in the study. |

c. | nothing about the statistical significance of the findings. |

d. | that scores for analysis came from independent groups of subjects. |

ANS: C

The “t” indicates the t value obtained from calculating the *t*-test; “df” indicates the degree of freedom. A “p” value would indicate the statistical significance.

There is not enough information to conclude this. The “t” indicates the t value obtained from calculating the *t*-test; “df” indicates the degree of freedom. A “p” value would indicate the statistical significance.

There is not enough information to conclude this. The “t” indicates the t value obtained from calculating the *t*-test; “df” indicates the degree of freedom. A “p” value would indicate the statistical significance.

There is not enough information to conclude this. The “t” indicates the t value obtained from calculating the *t*-test; “df” indicates the degree of freedom. A “p” value would indicate the statistical significance.

DIF: Cognitive level: Application REF: p. 404

- What statistical test would you use to simultaneously test the difference between temperatures of four groups of subjects?

a. | ANOVA |

b. | Chi-square |

c. | t-test for dependent samples |

d. | t-test for independent samples |

ANS: A

Analysis of variance is used to test for difference between means and can examine data from two or more groups simultaneously.

Chi-square determines whether two variables are independent or related.

*t-tests* should not be used for multiple groups simultaneously.

*t-tests* should not be used for multiple groups simultaneously.

DIF: Cognitive level: Application REF: p. 406

- Which test statistic is calculated in analysis of variance (ANOVA)?

a. | r |

b. | F |

c. | t |

d. | X^{2} |

ANS: A

The results of ANOVA are reported as an *F* statistic.

The r represents a correlation coefficient.

The *t-test* is used to determine if there is a significant difference between groups with data measured at the interval or ratio level.

Chi-square determines whether two variables are independent or related.

DIF: Cognitive level: Knowledge REF: p. 406

- Which of the following is an example of a dependent group?

a. | Chemotherapy recipients randomly assigned to receive either a new antiemetic drug or normal care |

b. | Nurses practicing in the hospital setting evaluated against those in community settings |

c. | Patients in cardiac rehabilitation measured for outcomes before and after completion of the program |

d. | Students involved in volunteer activities in a BSN program compared with those in an ADN program |

ANS: C

In dependent groups, subjects or observations selected for data collection are related in some way to the selection of other subjects or observations.

The two groups resulting from the random selection would be different from each other. In dependent groups, subjects or observations selected for data collection are related in some way to the selection of other subjects or observations.

The two groups of nurses are different and not related to one another. In dependent groups, subjects or observations selected for data collection are related in some way to the selection of other subjects or observations.

There is no relationship between the groups in the BSN program and the ADN program. In dependent groups, subjects or observations selected for data collection are related in some way to the selection of other subjects or observations.

DIF: Cognitive level: Application REF: p. 392

- Increasing the size of the sample can have an effect on the:

a. | alpha level. |

b. | internal consistency. |

c. | measurement error. |

d. | Type II error. |

ANS: D

A Type II error occurs when the null hypothesis is regarded as true when in fact it is false. A small sample size can contribute to a Type II error. Increasing the sample size can minimize the likelihood of a Type II error.

Alpha level is the level of significance decided upon by the researcher.

The internal consistency of a study is not dependent on sample size.

Measurement error can occur with any sample size.

DIF: Cognitive level: Application REF: p. 382

- In interpreting findings of a study, the researcher should:

a. | avoid discussion of problems encountered while doing the study that might influence outcomes. |

b. | emphasize that statistically significant findings must be incorporated into practice. |

c. | relate findings back to the purpose and framework of the study. |

d. | speculate about what the findings might mean to nursing practice. |

ANS: C

Findings in a study are the translated and interpreted results of the data analysis. Results of the data analysis must be interpreted by attaching meaning to the findings. This meaning should be interpreted in light of the study framework and be consistent with the original purpose of the study.

Discussion of problems encountered with the research can be very helpful to future researchers in the area.

Incorporation of findings into practice would be encouraged in the discussion section.

Speculation about the possible meaning of the findings is presented in the conclusion section.

DIF: Cognitive level: Synthesis REF: p. 410

- Nonsignificant findings are interpreted to mean the:

a. | differences between the groups are of little importance clinically. |

b. | groups are not statistically different. |

c. | study did not detect any differences between groups. |

d. | study results approached significance, but were not mathematically supported. |

ANS: C

Nonsignificant results do not mean no relationships exist among the variables; they indicate the study failed to find any. Nonsignificant results provide no evidence of either the truth or the falsity of the hypothesis.

Nonsignificant results do not mean no relationships exist among the variables; they indicate the study failed to find any.

The findings in any study are never absolute. Nonsignificant results do not mean no relationships exist among the variables; they indicate the study failed to find any.

This cannot be said without further information. Nonsignificant results do not mean no relationships exist among the variables; they indicate the study failed to find any.

DIF: Cognitive level: Knowledge REF: p. 383

- Which of the following study results are most common?

a. | Mixed results |

b. | Nonsignificant results |

c. | Significant and predicted results |

d. | Unexpected results |

ANS: A

Mixed results are the most common outcome of studies.

Mixed results are more common than nonsignificant results. Mixed results are the most common outcome of studies.

Mixed results are more common than significant results. Mixed results are the most common outcome of studies.

Unexpected results are usually relationships found between variables that were not hypothesized and not predicted from the framework being used. Mixed results are the most common outcome of studies.

DIF: Cognitive level: Knowledge REF: pp. 410-411

- Unexpected results are best dealt with in which of the following ways?

a. | Included in the final report |

b. | Incorporated into the ongoing study |

c. | Ignored because they are suspect findings |

d. | Interchanged with the dependent variable |

ANS: A

Unexpected results can be useful in theory development or modification of existing theory and in the development of later studies. They are also useful in developing the implications of the study.

The study methodology should not change because of unexpected findings.

Sometimes unexpected results can become very important findings in a study.

The dependent variable should remain as planned throughout the study.

DIF: Cognitive level: Analysis REF: p. 410

- A researcher notes that although no mathematical significance was foundRemember,me premature infants who were exposed to soothing music for 6 hours daily exhibited lower heart rates and less crying. This finding would have which type of significance?

a. | Clinical |

b. | General |

c. | Inferential |

d. | Statistical |

ANS: A

Clinical significance is related to the practical importance of findings, whereas statistical significance addresses the mathematical findings following statistical analysis of data.

The finding may or may not have general significance.

Further testing would be required before any inferences could be made.

No mathematical significance means no statistical significance.

DIF: Cognitive level: Application REF: pp. 410-411

- One key difference between research and evaluation is the ability of the researcher to:

a. | control all extraneous variables. |

b. | generalize the results to a larger population. |

c. | predict the outcome based on probability factors. |

d. | remain objective during the research process. |

ANS: B

Research allows for data that can be interpreted and generalized to be collected systematically. Generalization extends the implications of study findings from a research sample to a larger population. Evaluation is generally limited in scope to a single situation or group.

Research studies cannot control for all extraneous variables.

Prediction is not the goal of all research.

Objectivity should be maintained in both instances.

DIF: Cognitive level: Synthesis REF: p. 413

- Which of the following are purposes of statistical analysis?

a. | Prove the research hypothesis to be true. |

b. | Examine the numerical data gathered in a study. Provide insight into the meaning of the data. |

c. | Determine correct protocols for clinical research. |

d. | Prove the validity of a nursing theory. |

ANS: B

Statistical analysis both examines numerical data and provides insight into its meaning.

Data analysis cannot prove the research hypothesis to be true; it can support the hypothesis.

Statistical analysis does not determine which protocols are best for a research study.

Statistical analysis cannot prove the validity of a nursing theory; it can provide support for the theory.

DIF: Cognitive level: Comprehension REF: p. 372

- In reviewing a research study, which of the following statements would indicate clear problems with the findings?

a. | “Descriptive statistics indicated confirmation of the generalizability of the findings.” |

b. | “From the random sample of 1500 subjects from 16 colleges and universities, it was determined that nursing students tend to eat healthier while studying for an exam than other undergraduate students.” |

c. | “The instrument selected has been used in many previous studies and has good reliability and validity.” |

d. | “The sample consisted of 5000 clients with hypertension cared for in primary care settings from around the county.” |

ANS: A

To justify generalizability of the results of confirmatory analyses, a rigorous research methodology is needed, including strong research design, reliable and valid measurement methods, and a large sample size. Descriptive statistics are not inferential statistics; they only describe the situation.

The large sample size gleaned from several colleges and universities helps make the results generalizable to the population.

The use of valid and reliable instruments strengthens the results of the study, increasing its generalizability.

The large sample size from many clinics strengthens the results of the study, increasing its generalizability.

DIF: Cognitive level: Synthesis REF: p. 413

- A recent research study investigating weight loss in the morbidly obese, found a statistically significant (
*p*= 0.01) difference between subjects who followed an individually planned diet regimen with aerobic exercise and those in the treatment group, who also followed an individually planned diet regimen with aerobic exercise, but in addition, took a new medication. The medication, though extremely costly, created an additional 12 pound weight loss over the 3-month trial. What recommendations would be expected to come from this study?

a. | Further research is suggested as the medication appears promising. |

b. | The findings are modest at best; the medication should not be recommended. |

c. | The medication can provide significant results for anyone needing to lose weight. |

d. | The expense is much too great to ever justify use of this medication. |

ANS: A

Further research is definitely needed; there was some statistically significant weight loss, but not enough to warrant recommendation since it was “extremely” expensive and yielded a very small additional loss over 3 months. Nonetheless, for some patients it still might be an option if cost was not a factor and the need for weight loss was high. Additional research might show a more clinically significant amount of weight loss attributable to the medication.

The statistical and clinical findings are significant. The cost of the medication can be offset by the total weight loss. Recommendation to use is based upon the benefit-risk review, including clinical and statistical significance.

The findings are generalizable to the morbidly obese; not to all who fall in the spectrum of being overweight.

The statistical and clinical findings are significant. The cost of the medication can be offset by the total weight loss. Recommendation to use is based on the benefit-risk review, including clinical and statistical significance.

DIF: Cognitive level: Synthesis REF: p. 415

- When preparing data for analysis, which of the following variables would not most likely be grouped for statistical analysis?

a. | Ounces of water consumed by new mothers |

b. | Race and ethnicity of nursing faculty members |

c. | Results of fasting blood sugar testing |

d. | Weight of student athletes |

ANS: B

Continuous variables are often grouped; discrete variable cannot be grouped. Race and ethnicity are discrete variables and cannot be grouped.

An “ounce” is a continuous measurement and can be grouped.

Blood sugar results are continuous measurements and can be grouped.

Weight is a continuous measurement and can be grouped.

DIF: Cognitive level: Analysis REF: p. 384

- Which of the following variables are not matched correctly with their probable grouping status (grouped or ungrouped) in a frequency distribution?

a. | Age—grouped |

b. | Gender—grouped |

c. | Marital status—ungrouped |

d. | Time—grouped |

ANS: B

Discrete variables are usually ungrouped, and continuous variables are often grouped

Age is a continuous variable and can be grouped.

Marital status is a discrete variable and cannot be grouped.

Time is a continuous variable and can be grouped.

DIF: Cognitive level: Analysis REF: p. 384

- The researcher’s own voice is heard most in which section of a study?

a. | Conclusions |

b. | Findings |

c. | Literature review |

d. | Results |

ANS: A

The researcher uses logical reasoning and creates a meaningful whole from the findings.

The findings are an exploration of what the results mean, although some of this involves the researcher’s opinion, there is not as much as in the conclusions section. The correct answer is conclusions. The researcher uses logical reasoning and creates a meaningful whole from the findings.

The literature review is a detailed report of previous research on the topic of interest. The correct answer is conclusions. The researcher uses logical reasoning and creates a meaningful whole from the findings.

The results section is a straightforward report of the statistical analysis. The correct answer is conclusions. The researcher uses logical reasoning and creates a meaningful whole from the findings.

DIF: Cognitive level: Comprehension REF: p. 410

- Research is reported in which the
*t*-test is used to make multiple comparisons within the groups established for the study. Which of the following statements would someone reading the research correctly include in a critique of the study?

a. | “The researcher did not appear to know how to make correct use of the t-test.” |

b. | “The t-test is the correct statistic to use when making comparisons between groups.” |

c. | “There is concern over a Type II error caused by the multiple use of t-tests.” |

d. | “With no mention of the Bonferroni procedure, it is difficult to judge the levels of significance.” |

ANS: D

It is appropriate to comment on the amount of information provided on the use of specific procedures, in regard to evaluating if significance has been reached.

Making statements alluding that the researcher lacks knowledge is inappropriate in a critique.

*t*-test is not the correct statistic to use when making comparisons between groups.

Type I errors are of more concern when there is a multiple use of *t*-tests.

DIF: Cognitive level: Synthesis REF: p. 372

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