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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Foundations of Data-Driven Decision Making | 20% | - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance |
| Topic 2: Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals |
| Topic 3: Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods |
| Topic 4: Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis |
| Topic 5: Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
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NEW QUESTION # 107
What is an omission error?
Answer: D
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 # 108
What is the purpose of the quality management principle of dedication to fact-based decision-making?
Answer: D
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 # 109
Which term describes a response that appears the greatest number of times compared to other responses in a survey?
Answer: A
Explanation:
Themodeis the value that appears most frequently in a dataset. In data-driven decision making, it is particularly useful for analyzing categorical or discrete survey data.
The median represents the middle value, the mean is the average, and outliers are extreme values. Because the question asks for the most frequently occurring response, the correct answer isA, mode.
NEW QUESTION # 110
What are two qualities of key performance indicators (KPIs)?
Choose 2 answers.
Answer: B,C
Explanation:
Key performance indicators (KPIs) are designed to measure progress toward strategic objectives. In data- driven decision making, effective KPIs arestable, meaningful, and aligned with organizational goalsrather than frequently changing.
One important quality of KPIs is that theycan be used for internal benchmarking, allowing organizations to compare performance across departments, time periods, or projects. This helps identify best practices and performance gaps.
Another defining characteristic is that KPIs often followSMART criteria-Specific, Measurable, Achievable, Relevant, and Time-bound. These criteria ensure KPIs are clearly defined and actionable.
KPIs are not meant to be easily changed, as frequent changes undermine consistency and comparability. They also require ongoing monitoring and maintenance to remain relevant and accurate.
Therefore, the correct answers areB and D.
NEW QUESTION # 111
The U.S. Postal Service wants to know if local first-class mail is being delivered within two days of postmark.
Which key performance indicator (KPI) should the Postal Service use?
Answer: D
Explanation:
On-time performanceis the most appropriate KPI for measuring whether mail is delivered within a specified timeframe. In data-driven decision making, KPIs must align directly with operational objectives.
The Postal Service's goal is to assess delivery timeliness. On-time performance measures the percentage of mail delivered within the expected service standard, making it a direct and objective indicator.
Customer satisfaction and employee morale provide valuable insights but do not directly measure delivery speed. Incentive performance rate is unrelated to delivery outcomes.
Therefore, the correct answer isC, on-time performance.
NEW QUESTION # 112
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