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| Section | Weight | Objectives |
|---|---|---|
| Probability & Statistical Inference | 20% | - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation - Probability rules, distributions, expected value |
| Decision Models & Prescriptive Analytics | 15% | - Quality & process improvement tools - Decision trees, payoff matrices, expected value - Optimization, sensitivity analysis |
| Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Simple & multiple linear regression - Forecasting & trend analysis |
| Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution |
| 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 # 21
A hospital wants to increase revenue by performing more surgeries each day. This can be accomplished by reducing the turnaround time between surgeries in operating rooms. What is this objective an example of?
Answer: C
Explanation:
This objective is best understood as a key performance indicator because it focuses on a measurable operational target that directly supports organizational performance. Reducing turnaround time between surgeries is a specific, trackable metric that can be monitored over time and linked to broader outcomes such as increased surgical volume, higher revenue, improved efficiency, and better use of operating room capacity.
A key performance indicator is designed to quantify progress toward an important goal, and this scenario fits that purpose clearly. A balanced scorecard is a broader strategic framework that includes multiple dimensions of performance rather than a single focused measure. A departmental income statement is a financial report, not an operational objective. A managerial directive may describe an instruction from leadership, but the question asks what the objective itself represents in performance management terms. Because the hospital is identifying a measurable factor tied to improvement and results, the correct answer is a key performance indicator.
NEW QUESTION # 22
A school board has nine voting members. Five members need to be chosen each year for the finance committee. Why should the combination technique be used when selecting committee members?
Answer: C
Explanation:
The combination technique is appropriate when selecting items or people from a group and the order of selection does not matter. In this case, five members are being chosen from nine voting members to serve on the finance committee. What matters is which five individuals are selected, not the sequence in which their names are chosen. Combinations are used precisely for this type of situation because they count unique groups without regard to arrangement. If order did matter, then a permutation approach would be required instead. The options referring to correlation and meeting attendance are unrelated to the mathematical reason for using combinations. This is a straightforward committee-selection problem, which is one of the most common applications of combinations in probability and counting methods. Recognizing whether order matters is the essential step in choosing between combinations and permutations. Since a finance committee is defined by its membership rather than by the order in which members were picked, the correct answer is that the selection order of committee members is not important.
NEW QUESTION # 23
Two vendors sell a dozen raw materials that a company needs to build its products. Which type of analysis should be used to determine if one of the vendors has a better average price at a given point in time?
Answer: C
Explanation:
To determine whether one vendor has a better average price than another, the company should use data analysis. This is the broad analytical approach that involves collecting pricing information, organizing the values, comparing averages, and possibly applying additional statistical methods to evaluate the difference.
The task is numerical and evidence-based, making data analysis the correct and most complete choice.
Heuristic analysis usually refers to rule-of-thumb decision methods rather than direct statistical comparison.
Background analysis is not the standard term for comparing measurable pricing information. Graphical analysis may help visualize price differences, but graphs alone do not fully describe the method needed to determine average pricing performance. Because the question asks which type of analysis should be used to compare average price, the answer is the one that directly refers to analyzing the numerical data itself.
Therefore, the correct answer is data analysis.
NEW QUESTION # 24
Research data indicate 95% confidence in a study in which subjects who were shown a product advertisement exhibited brand awareness compared to a control group who did not see the advertisement.
What can be concluded from this study?
Answer: B
NEW QUESTION # 25
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 # 26
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