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| Section | Weight | Objectives |
|---|---|---|
| Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance |
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution |
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive - Role of data in business decisions |
| Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Optimization, sensitivity analysis - Quality & process improvement tools |
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NEW QUESTION # 16
What must be analyzed using powerful analytic tools?
Answer: A
Explanation:
Big datamust be analyzed using powerful analytic tools due to its volume, velocity, and variety. In data- driven decision making, traditional tools are often insufficient for processing massive, complex datasets generated from digital platforms, sensors, and transactions.
Big data requires advanced computing power, specialized software, and sophisticated algorithms to extract meaningful insights. Inferential statistics and small datasets can often be handled with conventional statistical tools.
Therefore, the correct answer isC, big data.
NEW QUESTION # 17
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: D
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 # 18
Which two statements describe Ishikawa's seven basic tools of quality?
Choose 2 answers.
Answer: C,D
Explanation:
Ishikawa'sseven basic tools of qualitywere designed to be simple, visual, and accessible. In data-driven decision making, these tools help employees identify, analyze, and solve quality problems without requiring advanced statistical expertise.
The tools-such as flowcharts, histograms, Pareto charts, and cause-and-effect diagrams-represent processes graphically, making patterns and issues easier to understand. Additionally, they are intentionally designed so thatan average worker can easily understand and use them, supporting organization-wide quality improvement.
They do not rely on photographic representations, nor are they intended for advanced or expert-level training.
Instead, they empower frontline employees to participate in continuous improvement efforts.
Therefore, the correct answers areA and C.
NEW QUESTION # 19
What does big data include?
Answer: B
Explanation:
Big data includes both structured and unstructured data. Structured data are organized in predefined formats such as rows and columns in databases, spreadsheets, or transaction systems. Unstructured data include forms such as emails, videos, social media content, images, audio files, sensor outputs, and free-text documents that do not fit neatly into traditional tabular formats. One of the defining features of big data is not just its size, but also its variety. This variety means organizations must work with multiple data types and sources to generate useful insights. The other options do not define what big data includes. Spreadsheets may handle small portions of data, but they do not define the concept itself. Powerful extraction tools may be used in big data environments, but they are tools rather than components of the data. Inferential statistics are analytical methods, not the data itself. Therefore, the best answer is that big data includes both structured and unstructured data.
NEW QUESTION # 20
A company runs a regression analysis to determine sales based on advertising expenditures, which can be shown in a linear equation as y = 2x + 25,000. The company plans to spend $20,000 on advertising.
Which sales figure should the company expect to generate based on the given equation?
Answer: C
Explanation:
In linear regression, the equation y = mx + b is used to predict the value of the dependent variable based on the independent variable. In data-driven decision making, this equation represents the estimated relationship between advertising expenditure and sales revenue.
Here,xrepresents advertising spending,mis the slope (2), andbis the intercept ($25,000). Substituting the planned advertising expenditure of $20,000 into the equation gives:
y = 2(20,000) + 25,000
y = 40,000 + 25,000
y = 65,000
This result represents the expected sales revenue based on the regression model. The intercept indicates baseline sales when advertising spend is zero, while the slope shows the increase in sales for each additional dollar spent on advertising.
Therefore, the company should expect to generate$65,000in sales, making optionCthe correct answer.
NEW QUESTION # 21
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