D 514 Exam 1 V2 | D 514 Analytical
Methods of Healthcare Leaders | Actual
Q&A with Rationale (D514 Exam 1) |
Western Governors University
1. A healthcare administrator is reviewing patient wait times recorded in minutes. Which
level of measurement does this data represent?
A. Nominal
B. Ratio
C. Interval
D. Ordinal
Answer: B
Rationale: Wait time in minutes is a ratio level of measurement because it has a true zero
point. This means that a value of zero minutes represents the absence of a wait.
Additionally, the differences between values are meaningful, and ratios between values can
be calculated.
2. Which of the following is an example of nominal data in a clinical research setting?
A. Blood pressure
B. Pain scale 1-10
C. Body temperature
,D. Patient gender
Answer: D
Rationale: Nominal data represents categories that do not have an inherent numerical
order or rank. Patient gender classifies individuals into groups without implying one is
higher or lower than the other. This differs from ordinal data like pain scales or ratio data
like blood pressure.
3. A data set has a mean of 50 and a standard deviation of 5. According to the Empirical Rule,
what percentage of data falls between 40 and 60?
A. 95%
B. 68%
C. 99.7%
D. 50%
Answer: A
Rationale: The Empirical Rule states that for a normal distribution, approximately 95
percent of data falls within two standard deviations of the mean. In this case, two standard
deviations equal 10, making the range 40 to 60. Therefore, the vast majority of the data is
expected to reside within this interval.
4. In a hypothesis test, if the p-value is 0.03 and the alpha level is 0.05, what should the
researcher conclude?
A. Fail to reject the null hypothesis
, B. Accept the null hypothesis
C. Reject the null hypothesis
D. Change the alpha level
Answer: C
Rationale: Since the p-value is less than the established alpha level of 0.05, the results are
considered statistically significant. This indicates that there is sufficient evidence to reject
the null hypothesis in favor of the alternative. The probability of obtaining these results by
chance alone is low enough to warrant this action.
5. Which error occurs when a researcher rejects a null hypothesis that is actually true?
A. Sampling Error
B. Type II Error
C. Standard Error
D. Type I Error
Answer: D
Rationale: A Type I error is often referred to as a false positive, occurring when the null
hypothesis is wrongly rejected. This means the researcher concludes an effect exists when
it actually does not. The probability of this error is defined by the significance level, alpha.
6. When a test fails to reject a false null hypothesis, what type of error has been committed?
A. Type I Error
Methods of Healthcare Leaders | Actual
Q&A with Rationale (D514 Exam 1) |
Western Governors University
1. A healthcare administrator is reviewing patient wait times recorded in minutes. Which
level of measurement does this data represent?
A. Nominal
B. Ratio
C. Interval
D. Ordinal
Answer: B
Rationale: Wait time in minutes is a ratio level of measurement because it has a true zero
point. This means that a value of zero minutes represents the absence of a wait.
Additionally, the differences between values are meaningful, and ratios between values can
be calculated.
2. Which of the following is an example of nominal data in a clinical research setting?
A. Blood pressure
B. Pain scale 1-10
C. Body temperature
,D. Patient gender
Answer: D
Rationale: Nominal data represents categories that do not have an inherent numerical
order or rank. Patient gender classifies individuals into groups without implying one is
higher or lower than the other. This differs from ordinal data like pain scales or ratio data
like blood pressure.
3. A data set has a mean of 50 and a standard deviation of 5. According to the Empirical Rule,
what percentage of data falls between 40 and 60?
A. 95%
B. 68%
C. 99.7%
D. 50%
Answer: A
Rationale: The Empirical Rule states that for a normal distribution, approximately 95
percent of data falls within two standard deviations of the mean. In this case, two standard
deviations equal 10, making the range 40 to 60. Therefore, the vast majority of the data is
expected to reside within this interval.
4. In a hypothesis test, if the p-value is 0.03 and the alpha level is 0.05, what should the
researcher conclude?
A. Fail to reject the null hypothesis
, B. Accept the null hypothesis
C. Reject the null hypothesis
D. Change the alpha level
Answer: C
Rationale: Since the p-value is less than the established alpha level of 0.05, the results are
considered statistically significant. This indicates that there is sufficient evidence to reject
the null hypothesis in favor of the alternative. The probability of obtaining these results by
chance alone is low enough to warrant this action.
5. Which error occurs when a researcher rejects a null hypothesis that is actually true?
A. Sampling Error
B. Type II Error
C. Standard Error
D. Type I Error
Answer: D
Rationale: A Type I error is often referred to as a false positive, occurring when the null
hypothesis is wrongly rejected. This means the researcher concludes an effect exists when
it actually does not. The probability of this error is defined by the significance level, alpha.
6. When a test fails to reject a false null hypothesis, what type of error has been committed?
A. Type I Error
