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| Section | Objectives |
|---|---|
| Data-Driven Culture and Communication | - Building Data-Informed Organizations - Presenting Data Insights - Ethical Considerations in Data Use - Stakeholder Communication |
| Decision-Making Frameworks | - Risk Analysis and Assessment - Cost-Benefit Analysis - Evidence-Based Decision Making - Rational Decision Models |
| Data Analysis Fundamentals | - Data Quality and Cleaning - Data Types and Measurement Scales - Descriptive Statistics - Data Visualization Techniques |
| Business Intelligence and Analytics | - Key Performance Indicators (KPIs) - Dashboards and Reporting - Data Mining Concepts - Predictive Analytics Basics |
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NEW QUESTION # 90
A county government is creating a budget for the next fiscal year. They wish to use analytics to guide their decisions about costs.
Which analytic method can the county apply to this issue?
Answer: A
Explanation:
To guide budgeting decisions, data-driven decision making emphasizesbenchmarking against comparable organizations. Using theaverage cost per project spent by other similar countiesallows the county to assess whether its planned expenditures are reasonable and competitive.
Benchmarking provides external context that internal historical metrics cannot. While median costs or project counts describe internal performance, they do not indicate whether spending levels are appropriate relative to peers. Comparing average costs across similar counties helps identify inefficiencies, cost-saving opportunities, and realistic budget targets.
Therefore, optionAis the most effective analytic method for cost-based decision-making in this scenario.
NEW QUESTION # 91
What is the primary goal of Six Sigma?
Answer: D
Explanation:
The primary goal ofSix Sigmais tofoster a commitment to continuous improvementby systematically reducing defects and process variation. In data-driven decision making, Six Sigma uses statistical methods to improve quality, efficiency, and consistency across organizational processes.
Six Sigma emphasizes disciplined problem-solving through data analysis, root-cause identification, and process control. While reducing defects to 3.4 per million opportunities is a hallmark metric, the broader objective is embedding continuous improvement into organizational culture.
SIPOC is a supporting tool, leadership is a contributing factor, and collaborative planning forecasting and replenishment relates to supply chain management, not Six Sigma's core purpose.
Therefore, the correct answer isD.
NEW QUESTION # 92
How does Six Sigma relate to a firm's application of a control chart?
Answer: D
Explanation:
Six Sigma is a quality management methodology focused on reducing defects, minimizing variation, and improving process performance through data-driven analysis. Control charts are one of the statistical process control tools commonly used within Six Sigma because they allow firms to continually measure processes and outputs over time. By tracking data points against control limits, organizations can determine whether a process is operating normally or whether unusual variation requires investigation. This ongoing measurement supports the Six Sigma goal of achieving highly consistent performance and identifying sources of error early.
The other options do not accurately describe the relationship. Six Sigma is not equivalent to linear programming, which is an optimization technique. It also does not directly produce a balanced scorecard, which is a broader strategic performance framework. Although supplier and input reliability may matter in quality management, that is not the primary connection between Six Sigma and control charts. Therefore, the best answer is that Six Sigma continually measures processes and outputs through tools such as control charts.
NEW QUESTION # 93
Which quality management principle should team members apply?
Answer: C
Explanation:
A core principle of quality management is systems thinking, which emphasizes that organizations operate as interconnected processes rather than isolated tasks. Because of this, team members should analyze all adjustments made in one part of a system that may affect other parts of the system. This approach recognizes that a change intended to improve one area can unintentionally reduce quality, efficiency, or consistency elsewhere. Effective quality management requires understanding process interactions, cause-and-effect relationships, and the broader impact of operational decisions. Option A is incorrect because quality improvement usually seeks to streamline processes rather than add unnecessary steps. Option C is also incorrect because quality management is about coordination and continuous improvement, not encouraging competition between the organization and employees. Option D does not reflect a recognized quality principle and suggests a lack of operational discipline. Therefore, the correct principle is the one that promotes analysis of interdependence within the system, making option B the best answer.
NEW QUESTION # 94
Which two tools make it easier to detect an out-of-range error?
Choose 2 answers.
Answer: A,D
Explanation:
Out-of-range errors occur when a data value falls outside the allowable or expected limits for a variable.
Examples include a negative age, a score above the maximum possible value, or a date in an impossible format. The tools most useful for identifying such errors are relational databases and spreadsheets. Relational databases often include validation rules, field constraints, data types, and query capabilities that can detect impossible or invalid entries. For example, a database can restrict a field to numeric values within a set range or flag records that violate defined rules. Spreadsheets can also support error detection through conditional formatting, formulas, filters, data validation, and sorting features that make unusual values easier to spot.
Experimental studies and observational studies are research designs, not data-validation tools. They describe how data are collected, not how errors are detected in stored records. Because the question asks specifically for tools that make out-of-range errors easier to detect, the correct choices are the data-handling tools that support validation and review: relational databases and spreadsheets.
NEW QUESTION # 95
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