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NEW QUESTION # 29
What is the purpose of the quality management principle of dedication to fact-based decision-making?
Answer: A
Explanation:
The principle offact-based decision-makingemphasizes using reliable data and objective analysis rather than intuition or opinion. In data-driven decision making, this principle exists primarily toreduce bias and increase trust in organizational plans and decisions.
When decisions are grounded in verified data, assumptions are challenged, personal biases are minimized, and outcomes are more predictable. This builds confidence among stakeholders and supports transparency and accountability.
Customer loyalty, waste elimination, and quality effectiveness may be indirect benefits, but the core purpose is ensuring that decisions are objective, defensible, and evidence-based. Therefore, the correct answer isD.
NEW QUESTION # 30
A professional services firm is undergoing a business process improvement exercise to improve productivity, staff morale, and client satisfaction while also thinking about the overall long-term financial performance of the company.
Which performance tool would best meet this firm's objectives?
Answer: A
Explanation:
Thebalanced scorecardis the most appropriate performance tool for this scenario because it integrates financial and nonfinancial performance measuresinto a single framework. In data-driven decision making, the balanced scorecard supports a holistic view of organizational performance.
The firm's objectives include productivity (internal processes), staff morale (learning and growth), client satisfaction (customer perspective), and long-term financial performance (financial perspective). The balanced scorecard explicitly incorporates all these dimensions, ensuring alignment between strategic goals and operational execution.
Net promoter score focuses only on customer loyalty, results-based management emphasizes outcomes but lacks multi-perspective integration, and KPI dashboards may display metrics but do not inherently provide strategic balance.
Therefore, the correct answer isC, balanced scorecard.
NEW QUESTION # 31
What is an omission error?
Answer: C
Explanation:
Anomission erroroccurs whencrucial data is missingfrom a dataset, which can significantly compromise the quality of analysis and decision-making. In data-driven decision making, omission errors are a serious concern because missing information can lead to biased results, incorrect interpretations, and flawed conclusions.
Omission errors may arise during data collection, data entry, or data integration processes. For example, failing to record customer demographics, transaction values, or time periods can distort descriptive statistics and weaken predictive models. Unlike inaccuracies, which involve incorrect values, omission errors involve the absence of necessary data altogether.
Outliers represent extreme values and are not omission errors. Similarly, failing to review all data is a process issue rather than a data-quality error definition. Inaccurate data refers to incorrect or erroneous values, not missing ones.
Effective data quality management emphasizes identifying and correcting omission errors through validation rules, completeness checks, and data audits. In data-driven decision making, ensuring that all relevant data is captured is essential for producing reliable insights and supporting sound business decisions. Therefore, the correct answer isD, as an omission error occurs when crucial data is missing.
NEW QUESTION # 32
Which analytic used in healthcare is calculated as a proportion of new cases compared to person-time units?
Answer: D
Explanation:
Theincidence rateis a healthcare analytic calculated as the number ofnew casesof a condition divided by person-time units at risk. In data-driven decision making, this metric is essential for understanding how quickly new cases occur within a population over time.
Person-time accounts for both the number of individuals and the duration they are observed, making the incidence rate particularly useful when populations are dynamic or when observation periods vary. This distinguishes incidence rate from cumulative incidence, which measures new cases over a fixed population and time period without person-time adjustment.
Prevalence measures existing cases at a point in time, and morbidity is a broader term describing illness burden rather than a specific rate calculation.
Because the question explicitly referencesnew cases compared to person-time units, the correct answer isB, incidence rate.
NEW QUESTION # 33
What is a basic assumption of a z-score?
Answer: A
Explanation:
Az-scorestandardizes a value by expressing how many standard deviations it lies from the mean. A fundamental assumption of z-score analysis in data-driven decision making is that the data can be transformed to astandard normal distributionwith amean of zero and a standard deviation of one.
This transformation allows analysts to compare values from different distributions on a common scale and to calculate probabilities using the standard normal table. The formula for a z-score subtracts the mean from the observed value and divides by the standard deviation, resulting in this standardized distribution.
Outliers are not eliminated by default in z-score calculations; instead, z-scores are often used to identify outliers. A standard deviation of 2 is incorrect and would not represent a standardized distribution.
Therefore, the correct answer isA, reflecting the core assumption underlying z-score usage.
NEW QUESTION # 34
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