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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Foundations of Data-Driven Decision Making | 20% | - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance - Role of data in business decisions |
| Topic 2: Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance |
| Topic 3: Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards |
| Topic 4: Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation - Probability rules, distributions, expected value |
| Topic 5: Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
>> Data-Driven-Decision-Making Pass Rate <<
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NEW QUESTION # 37
Amusement Park W is in California. Amusement Park X is in Texas. A survey asks 1,000 people living in California if they prefer Amusement Park W or X.
Which problem exists with this survey?
Answer: C
Explanation:
The primary problem with this survey issystematic error, which occurs when the data collection process consistently favors certain outcomes due to flawed design. In data-driven decision making, systematic error arises when a sampling method introduces bias that skews results in a predictable direction.
In this scenario, surveying only people living in California creates a location-based bias. Respondents are far more likely to prefer Amusement Park W because it is geographically closer, more familiar, and more accessible than Amusement Park X in Texas. This bias does not occur randomly; instead, it systematically influences responses toward one option, making the results unreliable for comparing overall preferences between the two parks.
Random error would involve unpredictable variation, which is not the issue here. Measurement bias relates to how questions are asked or measured, and information bias concerns inaccurate or misleading data reporting.
The core issue is thenon-representative sample, which violates the principle of unbiased data collection.
Data-driven decision making emphasizes that valid conclusions require representative samples. Because the survey design inherently favors one outcome, the results cannot be generalized, makingsystematic errorthe correct answer.
NEW QUESTION # 38
A major hospital system wants to improve its level of patient satisfaction. Management has recently asked patients to complete a survey as part of the discharge process. From this survey, a net promoter score is derived and tracked over time. What does a net promoter score reveal?
Answer: A
Explanation:
A net promoter score reveals the strength of an organization's customer relations by measuring how likely customers are to recommend the organization to others. In a hospital setting, patients are the relevant customer group, and their willingness to recommend the hospital reflects satisfaction, trust, and overall experience. Because the score is tracked over time, management can use it as an indicator of whether customer relationships are improving or declining. A higher net promoter score generally suggests stronger loyalty and more positive perceptions, while a lower score may indicate service or quality concerns. The score is not about how management feels about employees, nor is it used to track employee advancement. It may be influenced indirectly by marketing, but it does not primarily measure advertising campaign effectiveness. Its main purpose is to provide a clear signal about customer loyalty and relationship strength. Therefore, the correct answer is the strength of an organization's customer relations.
NEW QUESTION # 39
For which situation could a scatter diagram be used?
Answer: D
Explanation:
Ascatter diagramis used to visually examine therelationship between two quantitative variables. In data- driven decision making, scatter diagrams help analysts assess whether variables move together, whether the relationship is positive, negative, or nonexistent, and whether the relationship appears linear or nonlinear.
Each point on a scatter diagram represents a paired observation of two variables, such as advertising spend and sales revenue or hours studied and test scores. Patterns in the plotted points can suggest correlation, which may later be explored using regression analysis. Scatter diagrams are exploratory tools and do not, by themselves, establish causation.
A prioritization matrix ranks options, frequency differences are examined using bar or Pareto charts, and differences in means are evaluated using hypothesis tests such as t-tests or ANOVA. Therefore, the correct application of a scatter diagram is to demonstraterelationships between variables, making optionBcorrect.
NEW QUESTION # 40
What is the primary goal of Six Sigma?
Answer: A
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 # 41
What is a primary objective of the Six Sigma quality management system?
Answer: B
Explanation:
A primary objective of Six Sigma is to reduce defects and process variation so extensively that operations move toward near-perfect performance. This is why the best answer is approaching perfection in manufacturing operations. Six Sigma is built on the idea that consistent measurement, disciplined process improvement, and statistical control can dramatically improve quality and efficiency. The goal is not absolute perfection in a literal sense, but very low defect rates and highly reliable outcomes. Producing a balanced scorecard is unrelated to the main objective of Six Sigma, as that is a strategic performance measurement framework. Establishing ISO 9000 standards is also different; ISO standards relate to quality system requirements, while Six Sigma is a methodology for improvement and defect reduction. Although Six Sigma projects may help managers organize improvement efforts, its primary purpose is not simply to provide a roadmap. Its central mission is achieving superior quality performance through continuous reduction of errors and variability. Therefore, the correct answer is approaching perfection in manufacturing operations.
NEW QUESTION # 42
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