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| Section | Weight | Objectives |
|---|---|---|
| Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value - Correlation vs. causation |
| Foundations of Data-Driven Decision Making | 20% | - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance - Role of data in business decisions |
| Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
| Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution - Data visualization: charts, graphs, dashboards |
>> Data-Driven-Decision-Making Exam Questions Vce <<
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NEW QUESTION # 38
A financial analyst theorizes that commute times increase as the percentage of land availability for homes in a city decreases. To test this theory, the analyst uses a regression analysis. Which analysis result is supportive of this analyst's theory?
Answer: A
Explanation:
A regression result is most supportive of a theory when it shows a strong relationship between the independent and dependent variables. In this case, the analyst believes that commute times rise as land availability for homes falls. Among the answer choices, an R-squared value of 0.90 provides the strongest support because it indicates that about 90 percent of the variation in commute times is explained by the regression model. This suggests a very strong model fit. By contrast, an R-squared value of 0.10 would indicate a weak explanatory relationship. The p-values of 0.50 and 1 do not support the theory because large p- values suggest that the regression coefficient is not statistically significant. In regression analysis, a low p- value typically supports the idea that the predictor variable has a meaningful relationship with the outcome variable. Since no low p-value is offered, the best supportive result among the choices is the high R-squared value. Therefore, the correct answer is 0.90 because it indicates the model strongly explains the observed pattern.
NEW QUESTION # 39
In an experimental study, researchers are testing a new flea preventive medication on dogs using a blind study. Dogs are treated with the new medication or with a placebo.
Who should know which dogs are given the medication or the placebo for this blind study?
Answer: C
Explanation:
In ablind study, the purpose is to reduce bias that may influence responses or outcomes. In data-driven decision making, a blind study is designed so thatsubjects and response gatherers do not knowwhich treatment is administered, while the researchers do retain this information to correctly manage and analyze the experiment.
In this scenario, dog owners and response gatherers should not know whether the dogs received the medication or a placebo, as this knowledge could influence reporting of outcomes or observations. However, researchers must know which treatment each dog receives to ensure proper administration, monitoring, and statistical analysis.
If neither researchers nor participants knew the assignments, the study would be classified as adouble-blind study, which is not stated here. Allowing owners or response gatherers to know treatment assignments would introduce bias and undermine experimental validity.
Therefore, in a blind study,only the researchersshould know which dogs received the medication or placebo, making optionCthe correct answer.
NEW QUESTION # 40
What is an appropriate management use of statistics?
Answer: C
Explanation:
An appropriate management use of statistics is **understanding the demographics of customers**, which supports informed, proactive decision-making. Data-driven decision making emphasizes using statistical analysis to explore patterns, characteristics, and trends that help organizations better understand their customers and markets.
Analyzing customer demographics such as age, income, location, and preferences allows managers to segment markets, tailor products, improve services, and allocate resources effectively. This use of statistics is descriptive and diagnostic in nature and directly supports strategic planning.
Ordering products for an entire region based on data from a single store is inappropriate due to lack of representativeness. Justifying decisions after implementation reflects misuse of statistics, as analytics should inform decisions beforehand, not rationalize them after the fact. Implementing changes solely based on survey response rate ignores the content and validity of responses.
Ethical data-driven decision making requires that statistics be used responsibly, transparently, and with appropriate context. Therefore, the correct answer is **A**, as understanding customer demographics represents a proper and effective use of statistics by management.
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NEW QUESTION # 41
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: B
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 # 42
A county government must increase trust among voters that their tallying machines are accurately calibrated to count their votes. Each department is tasked with creating an online marketing campaign; however, the budget for these campaigns is limited.
How can the county apply data analytic approaches to allocate funds to each department?
Answer: B
Explanation:
Allocating limited resources effectively requires identifying where needs and risks are greatest. In data-driven decision making,measuring voter complaints per departmentprovides a direct, objective indicator of trust issues and communication gaps.
Departments with higher complaint volumes may require greater outreach to restore voter confidence. Using this metric allows funds to be allocated where they will have the greatest impact. Benchmarking turnout rates does not isolate departmental needs, and surveys of controllers or employees introduce subjectivity rather than evidence-based prioritization.
Therefore, the correct answer isA.
NEW QUESTION # 43
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