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| Section | Weight | Objectives |
|---|---|---|
| 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 - Decision trees, payoff matrices, expected value - Quality & process improvement tools |
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution |
| Predictive Analytics & Regression | 20% | - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance - Simple & multiple linear regression |
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NEW QUESTION # 97
What is the purpose of linking strategy to performance assessment in an organization?
Answer: D
Explanation:
Linking strategy to performance assessment helps an organization define where it needs or desires to be and measure progress toward that target. This connection is essential because it ensures that performance metrics are not selected in isolation, but instead support the mission, goals, and priorities of the organization. When strategy and assessment are aligned, managers can evaluate whether operational efforts are contributing to desired outcomes, identify gaps between current and expected performance, and make better-informed decisions about improvement. The other options do not reflect the main purpose. Increasing data collection may occur, but it is not the central reason for linking strategy to assessment. Reducing action plans is not a valid objective, and translating the mission only for team players is too narrow and inaccurate. Strategic performance assessment creates direction, accountability, and clarity across the organization. Therefore, the correct answer is that it provides a target of where an organization needs or desires to be.
NEW QUESTION # 98
What is a statistical process control procedure for a drill manufacturer?
Answer: B
Explanation:
Statistical process control (SPC)focuses on monitoring production processes to ensure they remain within acceptable limits. In data-driven decision making, SPC uses control charts and statistical measures to detect variation and identify whether a process is operating as intended.
For a drill manufacturer, determining whether theweight of selected drills is within a tolerable rangeis a classic SPC activity. Consistent weight indicates stable materials and manufacturing processes, while deviations may signal defects or process drift.
Market segmentation and demand forecasting are strategic analytics tasks, not process control activities.
Collaborative planning forecasting and replenishment relates to supply chain coordination rather than manufacturing quality control.
Therefore, the correct answer isB, as SPC is concerned with maintaining process consistency and product quality.
NEW QUESTION # 99
The daily sales from a salon are normally distributed with a mean of $1,500 and a standard deviation of $250.
The salon owner notices that sales were $750 on a particular day.
Why should the owner be concerned about sales based on this scenario?
Answer: C
Explanation:
In a normal distribution, most observations fall withinthree standard deviations of the mean. This principle is central to data-driven decision making and statistical process control. Values outside this range are considered highly unusual and may indicate an underlying problem.
Here, the mean is $1,500 and the standard deviation is $250. Three standard deviations below the mean equals
$750 ($1,500 # 3 ร $250). Sales of exactly $750 fall at the extreme lower boundary, indicating an unusually low sales day.
Such an outcome signals a potential anomaly that warrants investigation, such as operational issues, staffing shortages, or external disruptions. Values this far from the mean occur very infrequently in normal conditions.
Therefore, the owner should be concerned because sales of $750 areoutside the typical operating range, making optionCthe correct answer.
NEW QUESTION # 100
Which two characteristics must a researcher consider concerning data quality when ensuring that an analysis is based on a clean data set?
Choose 2 answers.
Answer: A,D
Explanation:
When evaluating whether a data set is clean enough for analysis, a researcher must focus on data quality dimensions that directly affect validity and usefulness. Two important characteristics are uniqueness and relevance. Data elements must be unique to prevent duplicate records from distorting counts, averages, totals, and trend analyses. Duplicate entries can lead to biased results, especially in customer, transaction, or survey data. Relevance is equally important because even accurate data are not helpful if they do not pertain to the question being studied. A clean data set should support the actual purpose of the analysis rather than merely being complete or large. The statement about age is incorrect because timeliness often matters; outdated data may no longer reflect the current environment. The statement that data cannot contain outliers is also too absolute. Outliers may be valid observations and can sometimes reveal important conditions, anomalies, or data-entry problems that require investigation rather than automatic removal. Thus, the best two characteristics are uniqueness and relevance, because both directly support meaningful, accurate, and decision- ready analysis.
NEW QUESTION # 101
How does a balanced scorecard (BSC) differ from a key performance indicator (KPI)?
Answer: D
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 # 102
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