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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation - Probability rules, distributions, expected value |
| Topic 2: Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Quality & process improvement tools - Optimization, sensitivity analysis |
| Topic 3: Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Forecasting & trend analysis - Interpreting coefficients, R-squared, significance |
| Topic 4: Statistical Concepts & Descriptive Analytics | 25% | - Measures of central tendency, dispersion, distribution - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards |
| Topic 5: Foundations of Data-Driven Decision Making | 20% | - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive - Ethics, privacy, and data governance |
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NEW QUESTION # 120
How is a cost-benefit analysis different in the public and private sectors?
Answer: A
Explanation:
Cost-benefit analysis differs between the public and private sectors primarily because the goals of the two sectors are different. In the public sector, decisions are generally evaluated in terms of the general welfare of the population, including social value, public health, safety, infrastructure, education, and broader community outcomes. In the private sector, cost-benefit analysis is usually more focused on profitability, financial return, efficiency, and shareholder value. While both sectors consider costs and benefits, the definition of "benefit" often changes depending on the mission of the organization. Public-sector benefits may include social improvements that do not generate direct profit, whereas private-sector benefits are often measured through revenue, cost savings, or market performance. The other options are too narrow or incorrect because they suggest one-sided attention to only cost or only benefits. Therefore, the best answer is that the public sector usually focuses on the general welfare of the population, whereas the private sector usually focuses on profits.
NEW QUESTION # 121
When researchers are studying the effect of new drug treatments on patients, bias can be introduced by patients if they are aware of who receives the placebo.
Which type of research design eliminates this type of bias?
Answer: C
Explanation:
Ablind studyis specifically designed to eliminate bias that occurs when participants are aware of treatment assignments. In data-driven decision making and experimental research, patient awareness of receiving a placebo or treatment can influence reported symptoms, perceived effectiveness, and behavior, thereby biasing results.
In a blind study, participants do not know whether they are receiving the treatment or the placebo. This prevents expectations or beliefs from influencing outcomes and ensures that observed effects are attributable to the treatment itself rather than psychological or behavioral factors.
Observational studies and prospective cohort studies do not involve controlled assignment of treatments and therefore cannot eliminate this type of bias. Time series studies analyze data over time but do not address participant awareness of treatment allocation.
By preventing patients from knowing their treatment group, blind studies improve internal validity and support more accurate causal inference. Therefore, the correct answer isD, blind study.
NEW QUESTION # 122
What is the purpose of the quality management principle of dedication to fact-based decision-making?
Answer: B
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 # 123
What are two benefits of good data quality management in improving business decision-making?
Choose 2 answers.
Answer: C,D
Explanation:
Good data quality management plays a critical role in improving business decision-making by ensuring that data is accurate, complete, and reliable. One key benefit is that itensures there are no missing data points, which helps maintain data completeness. Missing data can distort results, reduce analytical power, and lead to incorrect conclusions, especially in descriptive and inferential statistics.
Another important benefit is that data quality managementmitigates undetected errors from the data-entry process. Errors such as duplicate entries, incorrect values, or inconsistent formats can significantly bias analysis if left unnoticed. Through validation checks, cleaning procedures, and governance standards, organizations reduce the risk of flawed insights.
While good data quality supports better analysis, it does not guarantee statistical significance, as significance depends on sample size, variability, and study design. Similarly, it does not necessarily make the statistical process faster; in fact, data cleaning can be time-consuming. However, it improves theaccuracy and trustworthinessof outcomes.
In data-driven decision making, high-quality data is essential because decisions are only as good as the data used to support them. Therefore, the correct answers areA and D.
NEW QUESTION # 124
What is a primary objective of the Six Sigma quality management system?
Answer: D
Explanation:
A primary objective of Six Sigma is to reduce defects and process variation so extensively that operations move toward near-perfect performance. This is why the best answer is approaching perfection in manufacturing operations. Six Sigma is built on the idea that consistent measurement, disciplined process improvement, and statistical control can dramatically improve quality and efficiency. The goal is not absolute perfection in a literal sense, but very low defect rates and highly reliable outcomes. Producing a balanced scorecard is unrelated to the main objective of Six Sigma, as that is a strategic performance measurement framework. Establishing ISO 9000 standards is also different; ISO standards relate to quality system requirements, while Six Sigma is a methodology for improvement and defect reduction. Although Six Sigma projects may help managers organize improvement efforts, its primary purpose is not simply to provide a roadmap. Its central mission is achieving superior quality performance through continuous reduction of errors and variability. Therefore, the correct answer is approaching perfection in manufacturing operations.
NEW QUESTION # 125
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