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| Section | Weight | Objectives |
|---|---|---|
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution - Data visualization: charts, graphs, dashboards |
| Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis - Simple & multiple linear regression |
| Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value - Correlation vs. causation |
| Decision Models & Prescriptive Analytics | 15% | - Quality & process improvement tools - Optimization, sensitivity analysis - Decision trees, payoff matrices, expected value |
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NEW QUESTION # 26
How does a balanced scorecard (BSC) differ from a key performance indicator (KPI)?
Answer: B
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 # 27
What is a basic assumption of a z-score?
Answer: B
Explanation:
Az-scorestandardizes a value by expressing how many standard deviations it lies from the mean. A fundamental assumption of z-score analysis in data-driven decision making is that the data can be transformed to astandard normal distributionwith amean of zero and a standard deviation of one.
This transformation allows analysts to compare values from different distributions on a common scale and to calculate probabilities using the standard normal table. The formula for a z-score subtracts the mean from the observed value and divides by the standard deviation, resulting in this standardized distribution.
Outliers are not eliminated by default in z-score calculations; instead, z-scores are often used to identify outliers. A standard deviation of 2 is incorrect and would not represent a standardized distribution.
Therefore, the correct answer isA, reflecting the core assumption underlying z-score usage.
NEW QUESTION # 28
What are random errors caused by?
Answer: B
Explanation:
Random errors are caused by unpredictable fluctuations that occur naturally in measurement, observation, or recording processes. These errors are not consistently in one direction and do not systematically push results higher or lower. Instead, they introduce variability that can make repeated measurements differ slightly even when conditions seem similar. Examples include minor environmental changes, momentary variations in instrument sensitivity, normal human reaction differences, or small observational inconsistencies. Because random errors are unsystematic, they tend to average out over a large number of observations, although they still reduce precision. By contrast, an instrument that needs calibration is more closely associated with systematic error, because it may consistently overstate or understate measurements. Respondents favoring certain outcomes and biased data also reflect systematic forms of bias rather than random variation. In statistics and quality measurement, distinguishing between random error and systematic error is important because each requires a different response. Random error is mainly addressed through repetition, sample size, and statistical controls, whereas systematic error must be corrected at the source. Therefore, the correct cause of random errors is unpredictable fluctuations in readings.
NEW QUESTION # 29
Which term describes a response that appears the greatest number of times compared to other responses in a survey?
Answer: C
Explanation:
Themodeis the value that appears most frequently in a dataset. In data-driven decision making, it is particularly useful for analyzing categorical or discrete survey data.
The median represents the middle value, the mean is the average, and outliers are extreme values. Because the question asks for the most frequently occurring response, the correct answer isA, mode.
NEW QUESTION # 30
What happens when an organization focuses on customers?
Answer: D
Explanation:
A strong customer focus leads toincreased revenue and market share, which is a key principle in data- driven decision making and quality management. Organizations that prioritize customer needs are better positioned to deliver value, improve satisfaction, and build long-term relationships.
By understanding customer preferences, behavior, and feedback through analytics, organizations can tailor products and services more effectively. This alignment increases customer loyalty, repeat business, and positive word-of-mouth, all of which contribute to revenue growth and competitive advantage.
While focusing on customers may also improve efficiency, reduce bias, or lower costs, these outcomes are secondary benefits rather than the primary result. The most direct and measurable impact of customer focus is improved financial performance.
Therefore, the correct answer isC, as customer-focused organizations tend to experience higher revenue and expanded market share.
NEW QUESTION # 31
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