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| Section | Weight | Objectives |
|---|---|---|
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Hypothesis testing, p-values, confidence intervals - Correlation vs. causation |
| Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Optimization, sensitivity analysis - Quality & process improvement tools |
| Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution |
| Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis |
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive |
>> Data-Driven-Decision-Making専門知識訓練 <<
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質問 # 85
Which type of study is also known as a quasi-experimental study?
正解：A
解説：
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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質問 # 86
Which analytic used in healthcare is calculated as a proportion of new cases compared to person-time units?
正解：A
解説：
Theincidence rateis a healthcare analytic calculated as the number ofnew casesof a condition divided by person-time units at risk. In data-driven decision making, this metric is essential for understanding how quickly new cases occur within a population over time.
Person-time accounts for both the number of individuals and the duration they are observed, making the incidence rate particularly useful when populations are dynamic or when observation periods vary. This distinguishes incidence rate from cumulative incidence, which measures new cases over a fixed population and time period without person-time adjustment.
Prevalence measures existing cases at a point in time, and morbidity is a broader term describing illness burden rather than a specific rate calculation.
Because the question explicitly referencesnew cases compared to person-time units, the correct answer isB, incidence rate.
質問 # 87
A company runs a regression analysis to identify the impact of volume on demand, which can be shown as an equation y = 50x + 10. Which volume is needed to produce a demand of 10,510?
正解：B
解説：
To solve this regression problem, substitute the given demand value into the equation and solve for x. The equation is y = 50x + 10, and the desired demand is 10,510. Replacing y with 10,510 gives 10,510 = 50x + 10.
Subtracting 10 from both sides gives 10,500 = 50x. Dividing both sides by 50 gives x = 210. This means a volume of 210 is required to produce a demand of 10,510 under the linear relationship described by the equation. Regression equations are often used in forecasting and planning because they allow analysts to estimate one value from another. In this case, the independent variable is volume and the dependent variable is demand. The correct value must satisfy the equation exactly, and only 210 does so. The other options do not produce the required result when substituted into the equation. Therefore, the correct answer is 210.
質問 # 88
Which tool is often referred to as a fishbone chart or diagram?
正解：C
解説：
Thecause-and-effect diagram, also known as thefishbone diagramorIshikawa diagram, is used to identify potential causes of a problem. In data-driven decision making, it helps teams systematically explore root causes rather than focusing on symptoms.
The diagram visually organizes possible causes into categories such as people, processes, materials, machines, and environment. Histograms show distributions, flowcharts depict process steps, and scatter diagrams show relationships between variables.
Therefore, the correct answer isC, cause-and-effect diagram.
質問 # 89
A county government must increase trust among voters that their tallying machines are accurately calibrated to count their votes. Each department is tasked with creating an online marketing campaign; however, the budget for these campaigns is limited.
How can the county apply data analytic approaches to allocate funds to each department?
正解：C
解説：
Allocating limited resources effectively requires identifying where needs and risks are greatest. In data-driven decision making,measuring voter complaints per departmentprovides a direct, objective indicator of trust issues and communication gaps.
Departments with higher complaint volumes may require greater outreach to restore voter confidence. Using this metric allows funds to be allocated where they will have the greatest impact. Benchmarking turnout rates does not isolate departmental needs, and surveys of controllers or employees introduce subjectivity rather than evidence-based prioritization.
Therefore, the correct answer isA.
質問 # 90
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IT認証試験に合格したい受験生の皆さんはきっと試験の準備をするために大変悩んでいるでしょう。しかし準備しなければならないのですから、落ち着かない心理になりました。しかし、Tech4ExamのWGUのData-Driven-Decision-Makingトレーニング資料を利用してから、その落ち着かない心はなくなった人がたくさんいます。Tech4ExamのWGUのData-Driven-Decision-Makingトレーニング資料を持っていたら、自信を持つようになります。試験に合格しない心配する必要がないですから、気楽に試験を受けることができます。これは心のヘルプだけではなく、試験に合格することで、明るい明日を持つこともできるようになります。
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