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| Section | Objectives |
|---|---|
| Topic 1: Data Analysis Fundamentals | - Data Quality and Cleaning - Data Types and Measurement Scales - Descriptive Statistics - Data Visualization Techniques |
| Topic 2: Data-Driven Culture and Communication | - Stakeholder Communication - Ethical Considerations in Data Use - Presenting Data Insights - Building Data-Informed Organizations |
| Topic 3: Business Intelligence and Analytics | - Key Performance Indicators (KPIs) - Data Mining Concepts - Dashboards and Reporting - Predictive Analytics Basics |
| Topic 4: Decision-Making Frameworks | - Rational Decision Models - Cost-Benefit Analysis - Evidence-Based Decision Making - Risk Analysis and Assessment |
>> Data-Driven-Decision-Making시험대비자료 <<
Pass4Test의 WGU인증 Data-Driven-Decision-Making시험덤프는 고객님의 IT자격증을 취득하는 꿈을 실현시켜 드리는 시험패스의 지름길입니다. WGU인증 Data-Driven-Decision-Making덤프에는 실제시험문제의 거의 모든 문제를 적중하고 습니다. Pass4Test의 WGU인증 Data-Driven-Decision-Making덤프가 있으면 시험패스가 한결 간편해집니다.
질문 # 113
Why is quantitative analysis important to the decision-making process?
정답：B
설명：
Quantitative analysis is important in decision-making because it focuses on the systematic examination of measurable data, allowing organizations to evaluate situations objectively rather than relying only on intuition or personal judgment. A key strength of quantitative analysis is that it can examine and describe large sets of data in ways that reveal patterns, trends, relationships, and performance outcomes. This makes it especially useful in business, operations, finance, healthcare, and policy environments where decisions must be supported by evidence. By converting information into numbers, decision-makers can compare alternatives, estimate likely outcomes, and justify their choices with observable facts. While dashboards and surveys may support the process, they are not the fundamental reason quantitative analysis matters. Its real value lies in its ability to transform raw data into meaningful insights that improve planning, forecasting, risk evaluation, and resource allocation. Therefore, the best answer is the choice that identifies its central purpose: examining and describing large sets of data in a clear, measurable way.
질문 # 114
What is the basic difference between evaluating costs and benefits in the public and private sectors?
정답：C
설명：
The fundamental difference between cost-benefit evaluation in the public and private sectors lies inhow benefits are defined and measured. In data-driven decision making, private-sector projects primarily focus onrevenue generation and profitability, making optionCthe correct distinction.
Private organizations evaluate benefits using measurable financial outcomes such as revenue, profit margins, and return on investment. These metrics provide clear, quantifiable indicators of success. In contrast, public- sector projects often aim to maximizegeneral public welfare, including social, environmental, and economic benefits that are more difficult to quantify monetarily.
Public-sector benefits may include improved public health, safety, education, or trust in government- outcomes that do not translate directly into revenue. Therefore, while costs are measurable in both sectors, benefits differ substantially in nature.
Options A and B are incorrect because public-sector costs are not minimal and public benefits are often difficult to quantify. Option D incorrectly assigns public welfare to private projects. Thus, the correct answer isC.
질문 # 115
The daily sales from a salon are normally distributed with a mean of $1,500 and a standard deviation of $250.
The salon owner notices that sales were $750 on a particular day.
Why should the owner be concerned about sales based on this scenario?
정답：D
설명：
In a normal distribution, most observations fall withinthree standard deviations of the mean. This principle is central to data-driven decision making and statistical process control. Values outside this range are considered highly unusual and may indicate an underlying problem.
Here, the mean is $1,500 and the standard deviation is $250. Three standard deviations below the mean equals
$750 ($1,500 # 3 × $250). Sales of exactly $750 fall at the extreme lower boundary, indicating an unusually low sales day.
Such an outcome signals a potential anomaly that warrants investigation, such as operational issues, staffing shortages, or external disruptions. Values this far from the mean occur very infrequently in normal conditions.
Therefore, the owner should be concerned because sales of $750 areoutside the typical operating range, making optionCthe correct answer.
질문 # 116
A student is surveying chief executive officers to understand their levels of satisfaction with work-life balance over a period of three years. The student receives responses to a survey with a question regarding how many hours a week each CEO works. Which statistical approach should be used to summarize the data for analysis?
정답：C
설명：
The question asks how to summarize responses about how many hours each CEO works per week. Since hours worked is a numerical variable, a measure of central tendency is appropriate for summarizing the data.
The mean is the standard choice for describing the average number of hours worked across respondents. It provides a single representative value that can be used to understand the general workload pattern in the group. A bell curve is a distribution shape rather than a summary statistic. A scatterplot is a graphical tool used to display relationships between two quantitative variables, not to summarize one variable's central value. The median can also summarize numerical data, especially if there are strong outliers, but the most direct and standard summary for average hours worked is the mean unless the question specifically emphasizes skewness or resistance to outliers. Since the prompt asks for a statistical approach to summarize the data for analysis, the best answer is mean.
질문 # 117
A nonprofit organization is asking for donations. It hopes to design an email campaign that will ensure it receives at least $50,000. The campaign will reach 10,000 donors and receive donations with a mean of $10 and a standard deviation of $5.
Which measure should be used to determine the probability of the campaign receiving $50,000?
정답：C
설명：
To determine the probability of achieving a specific monetary threshold, data-driven decision making relies on standardization using the z-score. A z-score measures how many standard deviations a value is from the mean and allows analysts to calculate probabilities using the normal distribution.
In this scenario, the nonprofit wants to assess the likelihood that total donations will reach at least $50,000 given a known mean and standard deviation. The z-score enables conversion of the donation target into a standardized value, which can then be evaluated using probability tables or statistical software.
R-squared measures model fit in regression, the t-statistic is used in hypothesis testing, and the median does not support probability calculations. Therefore, the appropriate measure for determining probability in this context is thez-score, making optionDcorrect.
질문 # 118
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