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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
| Topic 2: Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods |
| Topic 3: Probability & Statistical Inference | 20% | - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value |
| Topic 4: 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 5: Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis |
>> Exam Data-Driven-Decision-Making Practice <<
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NEW QUESTION # 82
How is a cause-and-effect diagram used?
Answer: B
Explanation:
A cause-and-effect diagram, also known as an Ishikawa diagram or fishbone diagram, is used to brainstorm and organize possible root causes of a problem. It helps teams think systematically about why a problem may be occurring by grouping causes into logical categories such as methods, materials, people, equipment, and environment. In the scenario given, an intermittency problem suggests an issue that happens irregularly and may be difficult to isolate, which makes a cause-and-effect diagram especially useful. Its purpose is not to assign blame but to support structured problem-solving and root cause analysis. It is also not a financial risk tool or an automated software diagram generator. In quality management and data-driven improvement, this diagram encourages teams to explore multiple contributing factors before deciding on corrective action.
Therefore, the correct answer is that it is used to brainstorm possible root causes for an intermittency problem.
NEW QUESTION # 83
Which type of analysis determines whether there was a significant difference in the average donor solicitation amount between three nonprofit hospital events?
Answer: B
Explanation:
Analysis of Variance (ANOVA)is used to compare the means of three or more groups to determine whether statistically significant differences exist. In data-driven decision making, ANOVA is appropriate when evaluating differences across multiple categories.
In this scenario, the analyst is comparing average donor solicitation amounts across three separate events.
ANOVA tests whether at least one group mean differs from the others.
Cluster analysis groups data, time series examines trends over time, and logistic regression predicts categorical outcomes. Therefore, the correct answer isD, ANOVA.
NEW QUESTION # 84
What was the cumulative incidence rate during Year 2 at the university?
Answer: D
Explanation:
Cumulative incidence is the proportion of a population initially at risk that develops a condition during a specified period. It is commonly used in epidemiology to estimate the probability or risk of disease occurrence over time. In this question, the correct Year 2 cumulative incidence rate is 11.84 percent. This represents the proportion of individuals in the university population who developed the condition during that second year, based on the underlying at-risk population used in the original problem. Cumulative incidence is different from prevalence because it counts only new cases that arise during the stated interval rather than all existing cases. It also differs from incidence rate measures that incorporate person-time. Because the answer options are all percentages, the task is to identify the correct calculated proportion for Year 2. Based on the provided choices, 11.84 percent is the correct cumulative incidence value. Therefore, the correct answer is
11.84 percent.
NEW QUESTION # 85
Which statement is an accurate reflection of an analytical decision made by a for-profit organization?
Answer: A
Explanation:
A for-profit organization typically uses analytical methods to improve outcomes such as revenue, efficiency, market share, and especially profit. Among the available choices, linear programming is the recognized analytical optimization technique used to maximize or minimize an objective function subject to constraints.
In business settings, firms may use linear programming to optimize product mix, staffing, shipping routes, inventory allocation, advertising budgets, or production schedules. The purpose is to find the best possible decision based on limited resources such as time, labor, capital, or materials. The other options do not reflect standard analytical decision-making terminology in data-driven management. "Software programming" and
"hardware programming" refer to technology development activities, not profit-optimization methods, and
"social programming" does not describe a formal business optimization tool. Because the question asks for an accurate reflection of an analytical decision in a for-profit context, the correct answer is the one that uses a recognized prescriptive analytics method to optimize profit. That method is linear programming, which is widely used in operations research and managerial decision-making.
NEW QUESTION # 86
What is a disadvantage of a key performance indicator (KPI)?
Answer: C
Explanation:
A key performance indicator is useful because it provides a measurable way to track progress toward a goal, but one disadvantage is that it often focuses only on quantitative measures. This can be limiting because not every important aspect of organizational performance is easily captured in numerical form. For example, employee morale, trust, innovation culture, and relationship quality may be highly important but difficult to represent fully through a KPI. When managers rely too heavily on numerical indicators alone, they may overlook meaningful qualitative context or encourage behavior aimed at improving the metric rather than improving the underlying process. The other choices are less accurate. A KPI does not only indicate statistically significant change, and it does not inherently make data-driven measurement difficult. It can be used for both short-term and long-term objectives depending on design. The real weakness is that a KPI may oversimplify performance by emphasizing what can be counted rather than everything that matters. Therefore, the correct answer is that it only accounts for quantitative measures.
NEW QUESTION # 87
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