D 514 Exam 2 V3 | D 514 Analytical
Methods of Healthcare Leaders | Actual
Q&A with Rationale (D514 Exam 2) |
Western Governors University
1. A healthcare leader is reviewing a process and notices that the data points are consistently
within the control limits but show a non-random pattern. Which type of variation is most
likely present?
A. Systemic sampling bias
B. Common cause variation
C. Standard deviation error
D. Special cause variation
Answer: D
Rationale: Special cause variation is indicated by non-random patterns or data points
falling outside of established control limits. Even if points are within limits, a ‘run’ or ‘trend’
suggests an external factor is influencing the process. Healthcare leaders must identify
these causes to return the process to a state of statistical control.
2. When conducting a hypothesis test, what does the p-value specifically represent?
A. The probability that the alternative hypothesis is true.
B. The specific level of significance chosen by the researcher.
,C. The margin of error associated with the population mean.
D. The probability of observing the results, or more extreme results, if the null hypothesis
is true.
Answer: D
Rationale: The p-value is a measure of the evidence against the null hypothesis provided
by the sample data. A lower p-value indicates that the observed data is unlikely under the
assumption that the null hypothesis is correct. In healthcare analytics, a p-value below 0.05
is typically used to reject the null hypothesis in favor of the alternative.
3. In a linear regression analysis comparing hospital wait times (X) to patient satisfaction
scores (Y), the R-squared value is 0.75. How should this be interpreted?
A. 75% of the variation in wait times is explained by satisfaction scores.
B. Wait times cause 75% of the satisfaction scores.
C. 75% of the variation in satisfaction scores is explained by the variation in wait times.
D. There is a 75% chance that the correlation is statistically significant.
Answer: C
Rationale: R-squared, or the coefficient of determination, quantifies the proportion of
variance in the dependent variable that is predictable from the independent variable. An R-
squared of 0.75 indicates a strong relationship where the model explains a majority of the
variance. However, it is important to remember that R-squared does not imply a direct
cause-and-effect relationship.
, 4. Which statistical test is most appropriate for comparing the mean blood pressure of three
different groups of patients receiving different medications?
A. Paired t-test
B. One-way ANOVA
C. Independent t-test
D. Chi-square test of independence
Answer: B
Rationale: One-way Analysis of Variance (ANOVA) is used to determine if there are any
statistically significant differences between the means of three or more independent
groups. Using multiple t-tests instead of an ANOVA would increase the risk of a Type I
error. If the ANOVA is significant, post-hoc tests are then conducted to identify which
specific groups differ.
5. A hospital administrator commits a Type II error in a study regarding a new safety protocol.
What has occurred?
A. The administrator rejected a true null hypothesis.
B. The administrator used a sample size that was too large.
C. The administrator failed to reject a false null hypothesis.
D. The administrator incorrectly calculated the standard deviation.
Answer: C
Methods of Healthcare Leaders | Actual
Q&A with Rationale (D514 Exam 2) |
Western Governors University
1. A healthcare leader is reviewing a process and notices that the data points are consistently
within the control limits but show a non-random pattern. Which type of variation is most
likely present?
A. Systemic sampling bias
B. Common cause variation
C. Standard deviation error
D. Special cause variation
Answer: D
Rationale: Special cause variation is indicated by non-random patterns or data points
falling outside of established control limits. Even if points are within limits, a ‘run’ or ‘trend’
suggests an external factor is influencing the process. Healthcare leaders must identify
these causes to return the process to a state of statistical control.
2. When conducting a hypothesis test, what does the p-value specifically represent?
A. The probability that the alternative hypothesis is true.
B. The specific level of significance chosen by the researcher.
,C. The margin of error associated with the population mean.
D. The probability of observing the results, or more extreme results, if the null hypothesis
is true.
Answer: D
Rationale: The p-value is a measure of the evidence against the null hypothesis provided
by the sample data. A lower p-value indicates that the observed data is unlikely under the
assumption that the null hypothesis is correct. In healthcare analytics, a p-value below 0.05
is typically used to reject the null hypothesis in favor of the alternative.
3. In a linear regression analysis comparing hospital wait times (X) to patient satisfaction
scores (Y), the R-squared value is 0.75. How should this be interpreted?
A. 75% of the variation in wait times is explained by satisfaction scores.
B. Wait times cause 75% of the satisfaction scores.
C. 75% of the variation in satisfaction scores is explained by the variation in wait times.
D. There is a 75% chance that the correlation is statistically significant.
Answer: C
Rationale: R-squared, or the coefficient of determination, quantifies the proportion of
variance in the dependent variable that is predictable from the independent variable. An R-
squared of 0.75 indicates a strong relationship where the model explains a majority of the
variance. However, it is important to remember that R-squared does not imply a direct
cause-and-effect relationship.
, 4. Which statistical test is most appropriate for comparing the mean blood pressure of three
different groups of patients receiving different medications?
A. Paired t-test
B. One-way ANOVA
C. Independent t-test
D. Chi-square test of independence
Answer: B
Rationale: One-way Analysis of Variance (ANOVA) is used to determine if there are any
statistically significant differences between the means of three or more independent
groups. Using multiple t-tests instead of an ANOVA would increase the risk of a Type I
error. If the ANOVA is significant, post-hoc tests are then conducted to identify which
specific groups differ.
5. A hospital administrator commits a Type II error in a study regarding a new safety protocol.
What has occurred?
A. The administrator rejected a true null hypothesis.
B. The administrator used a sample size that was too large.
C. The administrator failed to reject a false null hypothesis.
D. The administrator incorrectly calculated the standard deviation.
Answer: C
