1
WGU D514 ANALYTICAL METHODS OF
HEALTHCARE LEADERS OA 2026/2027
Complete Objective Assessment | Actual
Questions & Verified Answers | Healthcare Data
Analytics & Leadership | Pass Guarantee
Section 1: Healthcare Data Analytics & Interpretation
Q1: A quality dashboard displays the monthly central-line associated bloodstream infection
(CLABSI) rate for the past 12 months. This is an example of:
A. Prescriptive analytics
B. Predictive analytics
C. Descriptive analytics
D. Diagnostic analytics
**Answer: C
Verified Rationale: Descriptive analytics summarizes historical data to show what has happened
over a defined period.
Q2: A predictive model forecasts emergency-department arrivals with 94 % accuracy for the next
7 days. Which technique is most commonly used for this time-series task?
A. Multiple linear regression
B. ARIMA
C. Chi-square test
D. DMAIC
**Answer: B
Verified Rationale: ARIMA (Auto-Regressive Integrated Moving Average) is the standard
method for forecasting serially correlated arrival data.
Q3: The pharmacy wants to identify the optimal reorder point for chemotherapy drugs that
minimizes both stock-outs and holding costs; this question requires:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
,2
**Answer: D
Verified Rationale: Prescriptive analytics recommends optimal actions (reorder points) under
constraints using techniques like linear programming.
Q4: A scatter-plot of BMI versus length-of-stay shows a correlation coefficient of +0.42. This
value indicates:
A. Strong negative linear relationship
B. Moderate positive linear relationship
C. Perfect positive linear relationship
D. No linear relationship
**Answer: B
Verified Rationale: r = 0.42 falls between 0.3–0.7, indicating a moderate positive linear
association.
Q5: Which visual best displays the distribution of patient satisfaction scores skewed to the left?
A. Pie chart
B. Histogram
C. Line graph
D. Scatter-plot
**Answer: B
Verified Rationale: A histogram reveals shape, center, and spread of a single continuous variable.
Q6: Select all that apply. Predictive analytics in healthcare typically require:
A. Clean, labeled historical data
B. Clinical expert input for feature selection
C. Randomized controlled trials for every model
D. Validation on unseen data
**Answer: A, B, D
Verified Rationale: RCTs are not mandatory for model building; clean data, expert features, and
external validation are essential.
Q7: A prescriptive model recommends staffing 8.3 RNs per shift. This output is most valuable
when paired with:
A. A Pareto chart of past medication errors
B. A sensitivity analysis on patient acuity changes
C. A run chart of historical census
D. A fishbone diagram of fall causes
**Answer: B
Verified Rationale: Sensitivity analysis shows how optimal staffing varies with acuity, supporting
robust decisions.
, 3
Section 2: Statistical Methods in Healthcare Decision-Making
Q8: A 95 % confidence interval for mean LOS is (3.8, 4.6) days. The best interpretation is:
A. 95 % of patients stay between 3.8 and 4.6 days
B. There is a 95 % probability the true mean is between 3.8 and 4.6 days
C. 95 % of sample means fall in this interval
D. The sample mean is 4.6 days
**Answer: B
Verified Rationale: A confidence interval estimates the plausible range for the unknown
population mean with stated confidence.
Q9: A two-tailed t-test on HbA1c improvement yields p = 0.03. At α = 0.05 we:
A. Fail to reject H₀
B. Reject H₀ and conclude the program was effective
C. Accept H₀
D. Conclude the program had no effect
**Answer: B
Verified Rationale: p < α provides sufficient evidence to reject the null hypothesis and support
the intervention’s efficacy.
Q10: In simple linear regression, the coefficient β₁ = –2.5 for age vs. pain score means:
A. Pain increases 2.5 points per year of age
B. Pain decreases 2.5 points per year of age
C. Age decreases 2.5 years per pain point
D. The correlation is –2.5
**Answer: B
Verified Rationale: β₁ quantifies the unit change in the dependent variable for each one-unit
increase in the predictor.
Q11: A chi-square test comparing readmission rates across three hospitals gives p = 0.12. The
appropriate conclusion is:
A. Rates differ significantly among hospitals
B. No significant difference is detected
C. The test had inadequate power
D. A t-test should follow
**Answer: B
Verified Rationale: p > 0.05 indicates no statistically significant association between hospital and
readmission.
Q12: Calculate the 95 % CI for a proportion: 25 infections in 400 central-line days. The z* value
is 1.96.
WGU D514 ANALYTICAL METHODS OF
HEALTHCARE LEADERS OA 2026/2027
Complete Objective Assessment | Actual
Questions & Verified Answers | Healthcare Data
Analytics & Leadership | Pass Guarantee
Section 1: Healthcare Data Analytics & Interpretation
Q1: A quality dashboard displays the monthly central-line associated bloodstream infection
(CLABSI) rate for the past 12 months. This is an example of:
A. Prescriptive analytics
B. Predictive analytics
C. Descriptive analytics
D. Diagnostic analytics
**Answer: C
Verified Rationale: Descriptive analytics summarizes historical data to show what has happened
over a defined period.
Q2: A predictive model forecasts emergency-department arrivals with 94 % accuracy for the next
7 days. Which technique is most commonly used for this time-series task?
A. Multiple linear regression
B. ARIMA
C. Chi-square test
D. DMAIC
**Answer: B
Verified Rationale: ARIMA (Auto-Regressive Integrated Moving Average) is the standard
method for forecasting serially correlated arrival data.
Q3: The pharmacy wants to identify the optimal reorder point for chemotherapy drugs that
minimizes both stock-outs and holding costs; this question requires:
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
,2
**Answer: D
Verified Rationale: Prescriptive analytics recommends optimal actions (reorder points) under
constraints using techniques like linear programming.
Q4: A scatter-plot of BMI versus length-of-stay shows a correlation coefficient of +0.42. This
value indicates:
A. Strong negative linear relationship
B. Moderate positive linear relationship
C. Perfect positive linear relationship
D. No linear relationship
**Answer: B
Verified Rationale: r = 0.42 falls between 0.3–0.7, indicating a moderate positive linear
association.
Q5: Which visual best displays the distribution of patient satisfaction scores skewed to the left?
A. Pie chart
B. Histogram
C. Line graph
D. Scatter-plot
**Answer: B
Verified Rationale: A histogram reveals shape, center, and spread of a single continuous variable.
Q6: Select all that apply. Predictive analytics in healthcare typically require:
A. Clean, labeled historical data
B. Clinical expert input for feature selection
C. Randomized controlled trials for every model
D. Validation on unseen data
**Answer: A, B, D
Verified Rationale: RCTs are not mandatory for model building; clean data, expert features, and
external validation are essential.
Q7: A prescriptive model recommends staffing 8.3 RNs per shift. This output is most valuable
when paired with:
A. A Pareto chart of past medication errors
B. A sensitivity analysis on patient acuity changes
C. A run chart of historical census
D. A fishbone diagram of fall causes
**Answer: B
Verified Rationale: Sensitivity analysis shows how optimal staffing varies with acuity, supporting
robust decisions.
, 3
Section 2: Statistical Methods in Healthcare Decision-Making
Q8: A 95 % confidence interval for mean LOS is (3.8, 4.6) days. The best interpretation is:
A. 95 % of patients stay between 3.8 and 4.6 days
B. There is a 95 % probability the true mean is between 3.8 and 4.6 days
C. 95 % of sample means fall in this interval
D. The sample mean is 4.6 days
**Answer: B
Verified Rationale: A confidence interval estimates the plausible range for the unknown
population mean with stated confidence.
Q9: A two-tailed t-test on HbA1c improvement yields p = 0.03. At α = 0.05 we:
A. Fail to reject H₀
B. Reject H₀ and conclude the program was effective
C. Accept H₀
D. Conclude the program had no effect
**Answer: B
Verified Rationale: p < α provides sufficient evidence to reject the null hypothesis and support
the intervention’s efficacy.
Q10: In simple linear regression, the coefficient β₁ = –2.5 for age vs. pain score means:
A. Pain increases 2.5 points per year of age
B. Pain decreases 2.5 points per year of age
C. Age decreases 2.5 years per pain point
D. The correlation is –2.5
**Answer: B
Verified Rationale: β₁ quantifies the unit change in the dependent variable for each one-unit
increase in the predictor.
Q11: A chi-square test comparing readmission rates across three hospitals gives p = 0.12. The
appropriate conclusion is:
A. Rates differ significantly among hospitals
B. No significant difference is detected
C. The test had inadequate power
D. A t-test should follow
**Answer: B
Verified Rationale: p > 0.05 indicates no statistically significant association between hospital and
readmission.
Q12: Calculate the 95 % CI for a proportion: 25 infections in 400 central-line days. The z* value
is 1.96.
