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| Section | Weight | Objectives |
|---|---|---|
| Decision Models & Prescriptive Analytics | 15% | - Optimization, sensitivity analysis - Quality & process improvement tools - Decision trees, payoff matrices, expected value |
| Foundations of Data-Driven Decision Making | 20% | - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance - Role of data in business decisions |
| Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance |
| Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value - Correlation vs. causation |
| Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards |
>> Data-Driven-Decision-Making Valid Test Questions <<
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NEW QUESTION # 83
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: D
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 # 84
For which situation could a scatter diagram be used?
Answer: B
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 # 85
How does a balanced scorecard (BSC) differ from a key performance indicator (KPI)?
Answer: C
Explanation:
Akey performance indicator (KPI)measures performance in asingle critical area, such as revenue growth or customer satisfaction. In contrast, abalanced scorecard (BSC)provides amulti-dimensional view of organizational performance, typically across financial, customer, internal process, and learning perspectives.
Data-driven decision making emphasizes that relying on a single metric can lead to incomplete or biased conclusions. The BSC addresses this by integrating multiple KPIs into a cohesive framework aligned with strategic objectives.
Therefore, optionAcorrectly explains the distinction between a KPI and a BSC.
NEW QUESTION # 86
Phone calls for a company are routed randomly to one of eight call centers. Six are based in the United States, and two are based in another country. What is the probability that an incoming call will be routed to a U.S.- based call center?
Answer: D
Explanation:
Probability is calculated as the number of favorable outcomes divided by the total number of possible outcomes, assuming each outcome is equally likely. In this case, there are eight call centers total, and six of them are located in the United States. Since calls are routed randomly, each call center has an equal chance of receiving an incoming call. Therefore, the probability that a call is routed to a U.S.-based call center is 6 out of 8. This fraction simplifies to 3 out of 4, which is equal to 0.75 or 75 percent. The answer choices 25 percent and 33 percent are too small because they do not match the proportion of U.S. call centers. The option 67 percent is closer but still incorrect, as 6 divided by 8 is not 0.67. This is a basic probability problem involving equally likely outcomes. Because six of the eight centers are in the United States, the correct probability is 75 percent.
NEW QUESTION # 87
A normally distributed data index of vehicle safety ratings has a mean of 100 and a standard deviation of 15.
What is the probability that a randomly selected vehicle safety score from the data set will be between 85 and
115?
Answer: B
Explanation:
The interval from 85 to 115 is exactly one standard deviation below and above the mean, since the mean is
100 and the standard deviation is 15. In a normal distribution, the empirical rule states that approximately 68 percent of observations fall within one standard deviation of the mean, about 95 percent fall within two standard deviations, and about 99.7 percent fall within three standard deviations. Because the range 85 to 115 corresponds to mean ± 1 standard deviation, the probability of selecting a score in that range is about 68 percent. Among the available options, 68.8 percent is the correct choice and best represents this probability.
The other values correspond to wider intervals: 95.4 percent is associated with two standard deviations and
99.7 percent with three. A value of 100 percent would imply every possible score lies in that range, which is not true for a normal distribution. Therefore, the correct answer is 68.8 percent because the question describes the one-standard-deviation interval around the mean.
NEW QUESTION # 88
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