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Statistics and Data Analysis for Nursing Research 2nd Edition By Denise F. Polit – Test Bank

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Statistics and Data Analysis for Nursing Research 2nd Edition By Denise F. Polit – Test Bank

Chapter 1

Introduction to Data Analysis in an Evidence-Based Practice Environment

1.1. Statistical skills can play an important role in nursing because they help nurses to:

  1. Calculate appropriate doses and clinical measurements
  2. Generate clinical questions

*c. Evaluate and generate research evidence for nursing practice

  1. Make better use of computers and the Internet

1.2. In the context of a quantitative study, a concept is called a(n):

  1. Operational definition

*b. Variable

  1. Statistic
  2. Parameter

1.3. An example of a variable is:

*a. Systolic blood pressure

  1. Pi (π)
  2. 52.5 kilograms
  3. Number of seconds in a minute

1.4. An example of a datum is:

  1. Systolic blood pressure
  2. Pi (π)

*c. 52.5 kilograms

  1. Number of seconds in a minute

1.5. Which of the following is not a component of a research question?

  1. An independent variable
  2. A population

*c. A sample

  1. A dependent variable

1.6. Identify the dependent variable in the following: In elderly men, what is the effect of chronic fatigue on level of depression?

  1. Age
  2. Sex
  3. Chronic fatigue

*d. Depression

1.7. Which of the following is a continuous variable?

  1. Number of pages in a book

*b. Age at death

  1. Falls during hospitalization
  2. Number of times married

1.8. Measurement is the assignment of numbers to characteristics of people or objects according to specified _________ . (Fill in the blank.)

*a. Rules

  1. Definitions
  2. Concepts
  3. Parameters

1.9. The measurement level that classifies attributes, indicates magnitude, and has equal intervals between values, but does not have a rational zero, is:

  1. Nominal
  2. Ordinal

*c. Interval

  1. Ratio

1.10. The measurement level that is sometimes called categorical or qualitative is:

*a. Nominal

  1. Ordinal
  2. Interval
  3. Ratio

1.11. It is not meaningful to calculate an arithmetic average with data from which of the following?

  1. Nominal measures
  2. Ordinal measures

*c. Nominal and ordinal measures

  1. All measures can be meaningfully averaged.

1.12. Degree of pain measured as none, a little, or a lot is measured on which of the following scales?

  1. Nominal

*b. Ordinal

  1. Interval
  2. Ratio

1.13. Body temperature is measured on which of the following scales?

  1. Nominal
  2. Ordinal

*c. Interval

  1. Ratio

1.14. Type of birth (vaginal or cesarean) is measured on the:

*a. Nominal scale

  1. Ordinal scale
  2. Interval scale
  3. Ratio scale

1.15. Which of the following is a ratio-level measure?

*a. Dietary cholesterol intake (mg)

  1. Cognitive impairment on a 50-item scale
  2. Pain on a 10-point scale
  3. Military rank

1.16. Ratio-level measures are different than any other level by virtue of which property?

  1. Classification
  2. Equal intervals between values

*c. A true, rational zero

  1. Indication of magnitude

1.17. Which level of measurement communicates the most information?

  1. Nominal
  2. Ordinal
  3. Interval

*d. Ratio

1.18. Researchers typically collect data from a ________ and hope to generalize their results to a _____________. (Fill in the blanks.)

  1. Population, sample
  2. Statistic, parameter
  3. Sample, statistic

*d. Sample, population

1.19. If the average amount of sleep for all people in the United States was 7.6 hours per night, this average would be a(n) _________ of the population of U.S. residents. (Fill in the blank.)

  1. Variable

*b. Parameter

  1. Statistic
  2. Datum

1.20. If a nurse researcher measured the anxiety level of 100 hospitalized children, the children’s average score on an anxiety scale would be a(n):

  1. Variable
  2. Parameter

*c. Statistic

  1. Operational definition

1.21. Statistical methods that are used to draw conclusions about a population are called:

*a. Inferential statistics

  1. Descriptive statistics
  2. Univariate statistics
  3. Multivariate statistics

Chapter 2

Frequency Distributions: Tabulating and Displaying Data

2.1. A major purpose of constructing a frequency distribution with sample data is to:

  1. Estimate a population parameter
  2. Test a research hypothesis

*c. Get an organized view of an entire set of scores

  1. Get experience with statistical software

2.2. In a frequency distribution, the two key informational components are:

*a. Score values (X), frequencies (f)

  1. A horizontal (X) axis, a vertical (Y) axis
  2. Frequencies (f), percentages (%)
  3. Participant ID number (id), score values (X)

2.3. In a frequency distribution, which of the following is true?

  1. Σ N = %
  2. Σ N = f
  3. Σ f = %

*d. Σ f = N

2.4. In the equation Σ % = 100.0, the symbol Σ signifies:

  1. A percentage

*b. The sum of

  1. A data value
  2. A frequency

2.5. In a frequency distribution, percentages are sometimes called:

  1. Proportions
  2. Relative proportions

*c. Relative frequencies

  1. Cumulative proportions

2.6. Data for which of the following variables is most likely to be presented in a grouped frequency distribution?

  1. Nursing specialty area

*b. Daily cholesterol intake

  1. Number of abortions
  2. Number of pets owned

2.7. The level of measurement for data appropriately presented in a bar graph is:

  1. Interval or ratio
  2. Nominal only
  3. Interval only

*d. Nominal or ordinal

2.8. In a frequency distribution graph, frequencies are typically presented on the ____ and data values are presented on the ____________. (Fill in the blanks.)

*a. Y axis, X axis

  1. X axis, Y axis
  2. f axis, N axis
  3. N axis, f axis

2.9. Which of the following sets of data is not unimodal?

*a. 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5

  1. 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4, 4, 4
  2. 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 3, 4, 5
  3. 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 5, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9

2.10. Which of the following variables is most likely to be negatively skewed in a general population?

  1. Number of times arrested

*b. Age at retirement

  1. Number of times married
  2. Age at birth

2.11. A normal distribution is not:

  1. Skewed
  2. Leptokurtic
  3. Platykurtic

*d. All of the above

2.12. A wild code is:

*a. A value that is impossible given the coding scheme

  1. An outlier or high value
  2. A code for which there is a very low frequency
  3. A code for which there is a very high frequency

The next eight questions pertain to the following table (Table 2):

Table 2

Number of Pregnancies of Study Participants

Frequency

Percentage

Cumulative Percentage

0

24

11.1

11.1

1

29

13.5

24.6

2

78

36.3

60.9

3

46

21.4

82.3

4

22

10.2

92.5

5

11

5.1

97.6

6

4

1.9

99.5

7

1

0.4

100.0

Total

215

100.0

2.13 In Table 2, the variable is _______ and the measurement level is _________. (Fill in the blanks.)

  1. Discrete, interval

*b. Discrete, ratio

  1. Continuous, interval
  2. Continuous, ratio

2.14. Table 2 is an example of a:

*a. Frequency distribution

  1. Grouped frequency distribution
  2. Class interval
  3. Data matrix

2.15. In Table 2, the value of N is:

  1. 24
  2. 100.0

*c. 215

  1. 7

2.16. In Table 2, the cumulative relative frequency for five or fewer pregnancies is:

  1. 210
  2. 199
  3. 92.5

*d. 97.6

2.17. The best way to graph information in Table 2 would be to construct:

*a. A histogram

  1. A pie chart
  2. A bar graph
  3. Either a pie chart or a bar graph

2.18. In Table 2, the distribution of data would be described as:

  1. Symmetric

*b. Positively skewed

  1. Negatively skewed
  2. It cannot be determined.

2.19. In Table 2, the distribution of data would be described as:

*a. Unimodal

  1. Bimodal
  2. Multimodal
  3. It cannot be determined.

2.20. In Table 2, the most likely number to be an outlier is:

  1. 0
  2. 1

*c. 7

  1. 24

Chapter 3

Central Tendency, Variability, and Relative Standing

3.1. A distribution of data values can be described in terms of all of the following characteristics except:

  1. Central tendency
  2. Variability

*c. Relative standing

  1. Shape

3.2. Central tendency indexes are all of the following except which of the following statements?

  1. They are descriptive statistics.

*b. They summarize how dispersed a set of scores is.

  1. They provide information about a value around which scores cluster.
  2. They are appropriate for interval- and ratio-level measures.

3.3. In the following distribution (10 11 12 13 14 15 15 15 15) the mode is:

  1. 11
  2. 12
  3. 14

*d. 15

3.4. In the following distribution (10 11 12 13 14 15 15 15 15) the median is:

  1. 11
  2. 12

*c. 14

  1. 15

3.5. The median is all of the following except:

  1. The 50th percentile
  2. The point that divides a distribution in half
  3. Q2

*d. The most popular score in the distribution

3.6. For which of the following set of numbers are the mean, median, and mode the same value?

*a. 1 2 3 3 4 4 4 4 4 5 5 6 7

  1. 1 1 2 2 3 3 4 4 5 5 6 6 7 7
  2. 1 1 1 2 3 3 4 4 5 5 6 7 7 7
  3. All of the above

3.7. In which type of distribution is the mean a higher value than the median or mode?

  1. A leptokurtic distribution

*b. A positively skewed distribution

  1. A negatively skewed distribution
  2. A normal distribution

3.8. If there are outliers at either end of a distribution that is symmetric, a researcher might:

*a. Calculate a trimmed mean

  1. Report the median rather than the mean
  2. Report the mode rather than the mean
  3. Omit the variable from further analyses

3.9. Which of the following indexes of dispersion is not in the original units of measurement of the variable?

  1. Range
  2. Interquartile range
  3. Standard deviation

*d. Variance

3.10. Which of the following indexes of dispersion tends to be least stable—most likely to fluctuate from one sample to another from the same population?

*a. Range

  1. IQR
  2. Standard deviation
  3. Variance

3.11. Which of the following indexes involves the calculation of deviation scores (x)?

  1. Range
  2. IQR

*c. SD

  1. M

3.12. Which of the following indexes involves the calculation of percentiles?

  1. z

*b. IQR

  1. SD
  2. M

3.13. Which of the following statistical symbols does not belong with the others?

  1. SD
  2. IQR
  3. M

*d. μ

3.14. What percentage of cases for a normally distributed variable lies within 1 SD above and below the mean?

  1. 34%
  2. 50%

*c. 68%

  1. 95%

3.15. In calculating standard scores, which two descriptive statistics are needed?

  1. Median, IQR
  2. Median, percentiles
  3. Mean, Range

*d. Mean, SD

3.16. A z score of 0.00 corresponds to an original score that:

  1. Could not be used in the calculation of the mean

*b. Is the same as the mean in the original distribution

  1. Is the lowest score in the original distribution
  2. Is an outlier

3.17. A z score of -1.00 corresponds approximately to a score for a normally distributed variable that is at the:

  1. 1st percentile
  2. 10th percentile

*c. 16th percentile

  1. 84th percentile

3.18. An extreme outlier is:

  1. More than 3 SDs above the mean
  2. Equivalent to a z score of -3.0 or lower, or +3.0 or higher
  3. More than three times the value of the mean

*d. More than 3 times the IQR, below Q1 or above Q3

3.19. In a boxplot, information about a distribution is depicted in terms of:

*a. Percentiles

  1. Standard deviation units
  2. z scores
  3. T scores

3.20. The number 100 can always be thought of as:

  1. A mean of a distribution when the SD is 15
  2. A value equivalent to the 10th percentile

*c. A number whose real limits are 99.5 and 100.5

  1. An outlier

Questions 3.21 through 3.25 pertain to the following table (Table 3):

Table 3

Characteristics of Chemotherapy Patients (N =100)

Characteristic

M (SD)

Mdn

Age (years)

48.9 (9.8)

47.0

Body mass index (BMI) (kg/m2)

27.0 (6.0)

25.1

Number of positive nodes

3.4 (2.9)

2.0

Dose of cyclophosphamide (mg)

1063.0 (477.0)

1250.0

Dose of doxorubicin (mg)

125.0 (53.0)

125.0

Degree of nausea, 0-100 scale

52.1 (25.0)

52.0

3.21. Refer to Table 3. For the variable body mass index, the variance is:

  1. 27.0
  2. 27.02
  3. 6.0

*d. 36.0

3.22. Refer to Table 3. For the variable number of positive nodes, the statistics suggest that the distribution is:

*a. Positively skewed

  1. Negatively skewed
  2. Symmetric
  3. Normal

3.23. Refer to Table 3. Assume that the distribution for the variable degree of nausea is normally distributed. In such a case, out of the 100 sample members, approximately how many gave a nausea rating of 77 or higher?

  1. 0
  2. 3

*c. 16

  1. 34

3.24. Refer to Table 3. Which variable in Table 3 is most likely to be negatively skewed?

  1. Age
  2. Body mass index

*c. Dose of cyclophosphamide

  1. Dose of doxorubicin

3.25. Refer to Table 3. For the variable body mass index, what would be the standard score for a person whose BMI was 21.0?

*a. -1.0

  1. 0.0
  2. 1.0
  3. 2.0

Chapter 4

Bivariate Description: Crosstabulation, Risk Indexes, and Correlation

4.1. Another name for a crosstab table is a:

  1. Scatterplot
  2. Frequency distribution

*c. Contingency table

  1. Relative risk table

4.2. In a 4 % 3 crosstab table, how many variables would there be?

*a. 2

  1. 4
  2. 7
  3. 12

4.3. In a 4 % 3 crosstab table, how many cells would there be?

  1. 2
  2. 4
  3. 7

*d. 12

4.4. Which measurement scale(s) are most amenable to crosstabulation?

  1. Nominal only

*b. Nominal and ordinal

  1. Nominal, ordinal, and interval
  2. Nominal, ordinal, interval, and ratio

4.5. A concept often used in connection with the calculation of all risk indexes is:

  1. EBP
  2. Crosstabulation

*c. Exposure to risk

  1. Odds

4.6. The two approaches to expressing amount of risk involve:

  1. Exposure and nonexposure
  2. Risk and risk reduction
  3. Odds and odds ratios

*d. Absolute risk and relative risk

4.7. A widely reported and intuitively appealing risk index for comparing risk outcomes is:

*a. Relative risk (RR)

  1. Absolute risk (AR)
  2. Odds ratio (OR)
  3. Number needed to treat (NNT)

4.8. The value of the RR is close to the value of the OR when:

  1. A retrospective case-control design was used

*b. Absolute risk reduction is modest

  1. Sample size is large
  2. Sample size is small

4.9. Risk indexes such as ARR, RR, OR, and NNT are not appropriate when:

  1. The study involves testing the effects of an intervention
  2. A prospective (cohort) design comparing risk groups is used

*c. The independent and/or dependent variable is not dichotomous

  1. The outcome is a nominal-level variable

4.10. The risk index that corresponds to a cell percentage in a crosstab table is:

*a. AR

  1. ARR
  2. RR
  3. RRR

4.11. When the value of RR is close to 1.0, this means that:

  1. The OR and the RR are far apart in value
  2. Absolute risk is low
  3. Exposure to the risk factor had a large effect on the outcome

*d. Exposure versus nonexposure to the risk factor is unrelated to the outcome

4.12. Pearson’s r is an index that communicates:

  1. Relative risk
  2. Relative risk reduction

*c. Correlation between two variables

  1. None of the above

4.13. If a scatterplot has data points that are tightly packed along a diagonal that slopes from the upper left to the lower right of the graph, the correlation between variables is:

  1. Strongly positive
  2. Weakly positive

*c. Strongly negative

  1. Weakly negative

4.14. Product–moment correlation coefficients are used to communicate information about:

  1. Risks
  2. Intervention effects
  3. The magnitude and direction of curvilinear relationships

*d. The magnitude and direction of linear relationships

4.15. Which of the following coefficients indicates the strongest relationship?

  1. .77

*b. -.89

  1. .00
  2. .50

4.16. If the value of r between X and Y is .90, what percentage of the variance in Y is explained by X?

  1. 0%
  2. 45%

*c. 81%

  1. .90%

4.17. For which of the following pairs of variables would it make sense to compute a product–moment correlation coefficient?

*a. Height and weight

  1. Race/ethnicity and height
  2. Race/ethnicity and marital status
  3. Marital status and weight

4.18. A researcher found a correlation of -.24 between scores on a self-esteem scale and number of alcoholic drinks consumed in the prior month. What does this mean?

  1. People who drank more alcohol had a slight tendency to have higher self-esteem.

*b. People who drank more alcohol had a slight tendency to have lower self-esteem.

  1. Drinking more alcohol tended to cause lower self-esteem.
  2. Having lower self-esteem tended to cause people to drink more alcohol.

4.19. How many variables are in a correlation matrix with four rows and four columns?

*a. 4

  1. 8
  2. 16
  3. It cannot be determined.

4.20. Which of the following values is likely to appear on the diagonal of a correlation matrix?

  1. -1.00
  2. .00
  3. .10

*d. 1.00

Questions 4.21 through 4.25 pertain to the following table (Table 4):

Table 4

Crosstabulation of Cognitive Impairment Status and Fall Incidence in Hospitalized Elders

Fall?

Total

Yes

No

Cognitive Impairment?

Yes

Count

% (within falls)

% (within impairment)

10

25.0%

50.0%

30

75.0%

25.0%

40

100.0%

No

Count

% (within falls)

% (within impairment)

10

10.0%

50.0%

90

90.0%

75.0%

100

100.0%

Total

Count

% (within falls)

% (within impairment)

20

14.3%

100.0%

120

85.7%

100.0%

140

100.0%

100.0%

4.21. Refer to Table 4. What percentage of elders in this sample had a fall?

*a. 14.3%

  1. 20.0%
  2. 25.0%
  3. 85.7%

4.22. Refer to Table 4. What numbers are in the denominator for calculating row percentages?

  1. 20, 120, 140
  2. 10, 10, 20

*c. 40, 100, 140

  1. 30, 90, 120

4.23. Refer to Table 4. What percentage of people who fell were not cognitively impaired?

  1. 0.0%
  2. 10.0%
  3. 14.3%

*d. 50.0%

4.24. Refer to Table 4. What was the absolute risk of falling for elders who were cognitively compared?

  1. .100
  2. .143

*c. .250

  1. .500

4.25. Refer to Table 4. In this example, what is the value of ARR?

  1. .100

*b. .150

  1. .250
  2. .500

Chapter 5

Statistical Inference

5.1. Probabilities are traditionally shown as values ranging from ____ to ____. (Fill in the blanks.)

  1. -1.00, +1.00

*b. .00, 1.00

  1. 0.0, 100.0
  2. -100.0, +100.0

5.2. On a 36-slot roulette wheel (that is, excluding values for “0” or “00”), what is the probability of a roulette spin yielding an even number?

  1. .028
  2. .25

*c. .50

  1. 1.00

5.3. What does the symbol H0 represent?

  1. A directional hypothesis
  2. A nondirectional hypothesis
  3. A research hypothesis

*d. A null hypothesis

5.4. Descriptive statistics are rarely exactly equal to population parameters because of:

*a. Sampling error

  1. Attrition bias
  2. Type I errors
  3. Type II errors

5.5. A sampling distribution of the mean is a distribution of:

  1. Population values from an entire population
  2. Sample values from a random sample

*c. Sample means from an infinite number of samples of a given size

  1. Sample values from a sample of samples of a given size

5.6. In a sampling distribution of the mean, which of the following is true?

  1. The mean is equal to 0.0.

*b. The mean is equal to the population mean.

  1. The distribution is a t distribution.
  2. The distribution is a binomial distribution.

5.7. The statistic referred to as the SEM is:

  1. The standard deviation of population values

*b. The standard deviation of a sampling distribution of means

  1. The standard error of measurement
  2. The standard estimate of the mean

5.8. The formula for estimating the SEM involves which two components?

  1. The mean and SD from a sample
  2. The mean and SD from the population
  3. The SD from a sample and number of cases in the population

*d. The SD from a sample and number of cases from that sample

5.9. Given a mean of 50.0 and an SD of 10.0, which of the following would have the smallest estimated SEM?

  1. A sample size of 50
  2. A sample size of 250

*c. A sample size of 500

  1. It cannot be determined without knowing the size of the population.

5.10. Because of an interest in precision, researchers prefer:

*a. Small SEMs

  1. Large SEMs
  2. A true SEM rather than an estimated SEM
  3. An SEM based on population rather then sample values

5.11. Which of the following statements is true?

  1. Parameter estimation is more frequently used by nurse researchers than hypothesis testing.
  2. Point estimation is preferred to interval estimation.

*c. Interval estimation involves constructing a confidence interval around a point estimate of a parameter.

  1. Estimation procedures are appropriate for estimating population means but not percentages.

5.12. Which of the following would be an element in the formula for computing confidence limits around a sample mean?

  1. The 95% CI

*b. A value from the t distribution for a specified sample size

  1. The value of 1.96, corresponding to z
  2. The sample SD

5.13. In the expression, M = 10.0, 95% CI = 8.0, 12.0, which of the following is true?

  1. There is a 5% probability that the population mean is greater than 12.0.

*b. There is a 2 ½% probability that the population mean is greater than 12.0.

  1. 95% of all population means are between 8.0 and 12.0.
  2. The population mean has a 95% probability of being 10.0.

5.14. The appropriate theoretical distribution for constructing confidence intervals around an odds ratio is:

  1. A sampling distribution of the mean
  2. A normal distribution
  3. A t distribution

*d. A binomial distribution

5.15. Which of the following is true regarding a 95% CI around a proportion?

  1. If the actual proportion is .00, the lower limit of the CI is a negative value.
  2. The theoretical distribution is more skewed when the proportion is .50 than when it is .10.

*c. The closer the proportion is to .50, the wider the CI.

  1. The larger the sample size, the wider the CI.

5.16. In hypothesis testing, which of the following is true?

*a. The null hypothesis is assumed to be true.

  1. Researchers seek to reject the null hypothesis with 100% certainty.
  2. p = 1.0 that a true null will be rejected or that a false null will be accepted.
  3. The null hypothesis is the same as the research hypothesis.

5.17. A Type I error:

  1. Is the inverse of power
  2. Means that the researcher has come to a false-negative conclusion
  3. Only occurs when the test is two tailed

*d. Has a risk of occurrence that is under the researchers’ control by designating α

5.18. The level of significance (significance criterion) of a statistical test:

  1. Is the power of the test to reject the null when it is false

*b. Is a probability level, typically .05

  1. Is a probability level, typically .95
  2. Is automatically computed when tests are performed by computer

5.19. The probability of committing a Type II error:

*a. Is greater when α is .01 than when α is .05

  1. Is always greater than the probability of committing a Type I error
  2. Is equivalent to 1 – α
  3. Is under the control of researchers by establishing a level for β

5.20. In a one-sample ­t-test:

  1. A sample mean for one group is tested against a sample mean for another group
  2. A sample mean is tested against the value of 50.0

*c. A sample mean is tested against a hypothesized value for the population mean

  1. A sample mean is tested against the population parameter

5.21. When a result is statistically significant, this means that:

*a. The result has a low probability of being due to chance factors

  1. The result is true
  2. The result is clinically important
  3. The result will be replicated in other similar studies

5.22. In a one-sample ­t-test, if the obtained t = -3.21 and the tabled t = 2.01 for α = .05, this means:

  1. The null hypothesis is wrong
  2. The null hypothesis is right
  3. The null hypothesis can be accepted

*d. The null hypothesis can be rejected

5.23. Which of the following two terms belong together?

  1. Null hypothesis, one-tailed test

*b. Directional hypothesis, one-tailed test

  1. Null hypothesis, two-tailed test
  2. Directional hypothesis, two-tailed test

5.24. Which of the following is an assumption of a parametric test?

  1. The central limit theorem is applicable.
  2. The population values follow a t distribution.

*c. The sample was randomly selected from the population.

  1. The risk of a Type I error is .05.

5.25. Nonparametric tests are more likely to be appropriate than parametric tests when:

*a. The dependent variable is severely skewed

  1. The dependent variable is measured on at least an interval scale
  2. The sample size is large
  3. Values in the population are normally distributed

5.26. A within-subjects test would be required in a study in which:

*a. Outcomes for a group are compared before and after an intervention

  1. Men are compared to women
  2. Lung cancer patients are compared to colon cancer patients
  3. Older participants are compared to younger ones

5.27. In a one-sample t-test for a study involving 200 study participants, df would equal:

  1. .05
  2. 1

*c. 199

  1. 200 % t

5.28. If a statistical test yields a p = .004, this means that:

  1. The probability is 4 in 100 that the research hypothesis is true
  2. The probability is 4 in 1,000 that the research hypothesis is true
  3. The probability is 4 in 100 that the null hypothesis is true

*d. The probability is 4 in 1,000 that the null hypothesis is true

Questions 5.29 through 5.32 pertain to the following table (Table 5), which presents fictitious results regarding factors associated with delayed extubation after cardiac surgery:

Table 5

Odds Ratios for Late Extubationa after Cardiac Surgery, by Patient Characteristics (N = 673)

Extubation < 5 Hours (%)

Extubation > 5 Hours (%)

OR

95% CI

Female patient

19.2

29.8

1.66

1.14 – 2.60

White patient

89.6

91.3

1.09

0.80 – 1.21

Hypertensive

62.7

73.9

1.58

1.09 – 2.24

Prior CABG

9.4

16.0

2.03

1.22 – 3.65

aLate extubation = More than 5 hours of mechanical ventilation

5.29. Refer to Table 5. Which of the following numbers is a point estimate for a risk index for delayed extubation?

  1. 19.2
  2. 29.8

*c. 1.66

  1. 1.14

5.30. Refer to Table 5. Which patient characteristic was most associated with a higher risk of delayed extubation?

  1. Sex
  2. Race
  3. Hypertensive status

*d. Prior experience with CABG

5.31. Refer to Table 5. What is the probability that the OR for delayed extubation for women is less than 1.14?

*a. .025

  1. .05
  2. .50
  3. .95

5.32. Refer to Table 5. Which patient characteristic was not associated with a significantly higher risk of delayed extubation?

  1. Sex

*b. Race

  1. Hypertensive status
  2. Prior experience with CABG

Chapter 6

t-Tests: Testing Two Mean Differences

6.1. A two-sample t-test would be appropriate for which of the following directional hypotheses?

  1. H1: M1M2
  2. H1: µ1 ≠ µ2

*c. H1: µ1 > µ2

  1. H1: M1 > M2

6.2. Which of the following is not an assumption for the t-test?

*a. Normally distributed variances in the populations

  1. Normally distributed score values in the populations
  2. Homogeneity of variances in the populations
  3. Random sampling of cases from the populations

6.3. Which of the following is true about t-tests?

  1. They are used when both the independent and dependent variable are nominal-level variables.

*b. They are used when the dependent variable is measured on an interval or ratio scale.

  1. They are robust to the violation of all assumptions as long as N is at least 30.
  2. They require measurements from people at least two points in time.

6.4. If cholesterol levels in twins were being compared, one of whom in each pair was randomly assigned to a special dietary intervention, the appropriate statistical test would be the:

  1. One-sample t-test
  2. Independent groups t-test
  3. Between-subjects t-test

*d. Dependent groups t-test

6.5. If smokers and nonsmokers were compared in terms of number of days absent from work annually, the appropriate statistical test would be the:

  1. One-sample t-test

*b. Independent groups t-test

  1. Paired t-test
  2. Dependent groups t-test

6.6. In a longitudinal study of 200 nursing school graduates, nurses who did not participate in the 3-year follow-up were compared to those who did. The appropriate statistical test would be the _____________ to assess for _____________ bias. (Fill in the blanks.)

  1. Independent groups t-test, selection

*b. Independent groups t-test, attrition

  1. Dependent groups t-test, cohort
  2. Dependent groups t-test, nonresponse

6.7. In the basic formula for the t-test, what is in the denominator?

*a. The standard error of the difference

  1. The variance of the difference
  2. The standard error of the mean
  3. The pooled standard deviation

6.8. A statistical test that can be used to test for the normality of a distribution is:

  1. The one-sample t-test
  2. The two-sample t-test
  3. Levene’s test

*d. The Kolgomorov-Smirnov test

6.9. A statistical test that can be used to test for equality of variances in the distributions for two groups is:

  1. The one-sample t-test
  2. The two-sample t-test

*c. Levene’s test

  1. The Kolgomorov-Smirnov test

6.10. A t was calculated to be -2.10 for a comparison of 50 men and 50 women with regard to attitude toward organ donation, measured on a 10-item scale. The tabled t for two-tailed α = .05 is 2.01. The researcher:

  1. Can accept the null hypothesis that men and women have comparable attitudes

*b. Can reject the null hypothesis that men and women have comparable attitudes

  1. Can accept the alternative hypothesis that men have more favorable attitudes
  2. Can accept the alternative hypothesis that women have more favorable attitudes

6.11. In a t-test situation, confidence intervals are constructed around:

*a. The difference between two means

  1. Each of the two means
  2. The pooled variance
  3. The two separate variances

6.12. In a t-test situation, magnitude of effects is often communicated through:

  1. The absolute value of the t statistic
  2. The p value
  3. The magnitude of Levene’s F

*d. The magnitude of Cohen’s d

6.13. Effect size indexes play a role in:

  1. Computing a confidence interval

*b. Integrating findings in a meta-analysis

  1. Testing the difference between two means
  2. Evaluating assumptions for a statistical test

6.14. With Cohen’s d, values are in what type of units?

  1. Probability values
  2. Raw data values

*c. Standard deviation units

  1. Mean difference units

6.15. Which of the following is not a component in a power analysis?

  1. The size of the sample

*b. The size of the population

  1. The effect size
  2. The significance criterion

6.16. In a post hoc power analysis, if the power estimate were .60 for a result that was nonsignificant, a researcher would be able to conclude that:

*a. The risk of having committed a Type II error was about 40%

  1. The risk of having committed a Type II error was about 60%
  2. The nonsignificant result was not correct
  3. The nonsignificant result was correct

Questions 6.17 through 6.20 pertain to the following table (Table 6), which presents fictitious results regarding the effects of guided imagery on pain outcomes among patients with cancer.

Table 6

Pain Outcomes for Cancer Patients Receiving a Guided Imagery Intervention (n = 100) Versus Those Receiving Usual Care (n = 100)

Outcome

Usual Care Group

Mean (SD)

Guided Imagery Group

Mean (SD)

t

p

d

Present pain intensity

5.3 (1.5)

4.7 (1.4)

3.24

.002

.41

Pain intensity—pain at its worst

8.5 (1.8)

8.3 (1.7)

1.29

.22

.12

Pain distress

6.8 (1.1)

5.8 (1.2)

5.34

<.001

.87

Pain interference

42.1 (6.1)

39.9 (6.0)

2.77

.02

.36

6.17. Refer to Table 6. Which statistical test is most likely being reported in this table?

  1. One-sample t-test

*b. Independent groups t-test, pooled variance formula

c Independent groups t-test, separate variance formula

  1. Dependent groups t-test

6.18. Refer to Table 6. For which outcome would the researcher need to accept the null hypothesis?

  1. Present pain intensity

*b. Pain intensity—pain at its worst

  1. Pain distress
  2. Pain interference

6.19. Refer to Table 6. What were the degrees of freedom in these analyses?

  1. 99
  2. 100

*c. 198

  1. 199

6.20. Refer to Table 6. Which of the following statements with regard to Table 6 is true?

  1. All of the effect sizes were in the small-to-moderate range, using Cohen’s guidelines.
  2. Because α was the same in all four analyses, power was also the same.

*c. Power was likely strongest for the outcome pain distress.

  1. Power was inadequate for all four analyses.

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