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| Section | Weight | Objectives |
|---|---|---|
| Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Optimization, sensitivity analysis - Quality & process improvement tools |
| Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Simple & multiple linear regression - Forecasting & trend analysis |
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution |
| Probability & Statistical Inference | 20% | - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, 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 |
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NEW QUESTION # 40
What is the purpose of the quality management principle of dedication to fact-based decision-making?
Answer: D
Explanation:
The principle offact-based decision-makingemphasizes using reliable data and objective analysis rather than intuition or opinion. In data-driven decision making, this principle exists primarily toreduce bias and increase trust in organizational plans and decisions.
When decisions are grounded in verified data, assumptions are challenged, personal biases are minimized, and outcomes are more predictable. This builds confidence among stakeholders and supports transparency and accountability.
Customer loyalty, waste elimination, and quality effectiveness may be indirect benefits, but the core purpose is ensuring that decisions are objective, defensible, and evidence-based. Therefore, the correct answer isD.
NEW QUESTION # 41
Which tool should be used to closely monitor inputs and outputs?
Answer: A
Explanation:
ASIPOC diagram(Suppliers, Inputs, Process, Outputs, Customers) is specifically designed to closely monitor and understand the flow of inputs and outputs within a process. In data-driven decision making and quality management, SIPOC diagrams provide a high-level view of how value is created and delivered.
By clearly identifying suppliers and inputs at the start of a process and outputs and customers at the end, organizations can assess whether inputs meet requirements and whether outputs align with customer expectations. This visibility helps identify inefficiencies, gaps, or quality issues early in the process lifecycle.
Business process diagrams focus on workflow steps but do not emphasize supplier-input and output- customer relationships. Financial statements and pro forma statements are financial planning tools and are not designed for operational process monitoring.
Therefore, the correct answer isC, SIPOC diagram.
NEW QUESTION # 42
What describes fact-based decision-making according to quality management principles?
Choose 2 answers.
Answer: A,C
Explanation:
Fact-based decision-making is a central quality management principle because it encourages organizations to rely on evidence, measurement, and analysis rather than assumptions or intuition alone. Decisions foster trust in plans when stakeholders can see that choices are grounded in objective information and sound reasoning.
This strengthens accountability and confidence in management actions. Fact-based decisions also help reduce external bias because they rely on verified information rather than opinions, pressure, or unsupported judgment. In contrast, decisions based only on the instincts of experienced leaders do not reflect the core meaning of fact-based management, even though experience may still be valuable. The statement about supplier relationships is not a defining description of fact-based decision-making and does not capture the principle itself. Quality management emphasizes using reliable data to guide planning, improve processes, and support consistent outcomes. Therefore, the two correct answers are that such decisions foster trust in plans and reduce external bias.
NEW QUESTION # 43
A boutique specializing in gifts reviews its sales data over the last year. It observes a slow decline in revenue in the first quarter, a growth in revenue in the second quarter, a slight decline in revenue in the third quarter, and a rapid increase in revenue in the fourth quarter.
Which data pattern type can the sales data be assessed against?
Answer: A
Explanation:
Seasonalityrefers to predictable patterns in data that repeat at regular intervals, such as quarters or months, due to seasonal factors. In data-driven decision making, identifying seasonal patterns helps organizations forecast demand and plan operations.
The boutique's revenue shows distinct quarterly patterns: declines and increases that align with different times of the year. The sharp increase in the fourth quarter is especially indicative of seasonal effects, such as holiday shopping.
Random variation and irregularity describe unpredictable fluctuations, while cyclicality refers to long-term economic cycles rather than recurring annual patterns. Therefore, the correct answer isC, seasonality.
NEW QUESTION # 44
Which type of study is also known as a quasi-experimental study?
Answer: B
Explanation:
A **quasi-experimental study** is commonly referred to as an **observational study** in data-driven decision making. Unlike true experiments, quasi-experimental studies do not involve random assignment of subjects to treatment and control groups. Instead, researchers observe outcomes in naturally occurring groups and attempt to draw conclusions about relationships between variables.
In observational studies, the researcher does not control the assignment of treatments. As a result, these studies are more susceptible to bias and confounding variables than randomized experiments. However, they are often necessary when controlled experimentation is impractical, unethical, or too costly. For example, studying the impact of policy changes or economic conditions typically relies on observational data.
Blind studies are a form of experimental design used to reduce bias, hypothesis testing is a statistical process rather than a study type, and content validity refers to measurement quality. None of these represent quasi- experimental designs.
In data-driven decision making, observational (quasi-experimental) studies are valuable for identifying associations and generating insights, but analysts must be cautious not to infer causality without proper controls. Therefore, the correct answer is **A**.
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NEW QUESTION # 45
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