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| Section | Objectives |
|---|---|
| Decision-Making Frameworks | - Evidence-Based Decision Making - Cost-Benefit Analysis - Rational Decision Models - Risk Analysis and Assessment |
| Data-Driven Culture and Communication | - Building Data-Informed Organizations - Stakeholder Communication - Presenting Data Insights - Ethical Considerations in Data Use |
| Business Intelligence and Analytics | - Key Performance Indicators (KPIs) - Data Mining Concepts - Predictive Analytics Basics - Dashboards and Reporting |
| Data Analysis Fundamentals | - Data Types and Measurement Scales - Data Visualization Techniques - Descriptive Statistics - Data Quality and Cleaning |
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質問 # 105
For which situation could a scatter diagram be used?
正解：B
解説：
Ascatter diagramis used to visually examine therelationship between two quantitative variables. In data- driven decision making, scatter diagrams help analysts assess whether variables move together, whether the relationship is positive, negative, or nonexistent, and whether the relationship appears linear or nonlinear.
Each point on a scatter diagram represents a paired observation of two variables, such as advertising spend and sales revenue or hours studied and test scores. Patterns in the plotted points can suggest correlation, which may later be explored using regression analysis. Scatter diagrams are exploratory tools and do not, by themselves, establish causation.
A prioritization matrix ranks options, frequency differences are examined using bar or Pareto charts, and differences in means are evaluated using hypothesis tests such as t-tests or ANOVA. Therefore, the correct application of a scatter diagram is to demonstraterelationships between variables, making optionBcorrect.
質問 # 106
What is a disadvantage of a key performance indicator (KPI)?
正解：D
解説：
A key performance indicator is useful because it provides a measurable way to track progress toward a goal, but one disadvantage is that it often focuses only on quantitative measures. This can be limiting because not every important aspect of organizational performance is easily captured in numerical form. For example, employee morale, trust, innovation culture, and relationship quality may be highly important but difficult to represent fully through a KPI. When managers rely too heavily on numerical indicators alone, they may overlook meaningful qualitative context or encourage behavior aimed at improving the metric rather than improving the underlying process. The other choices are less accurate. A KPI does not only indicate statistically significant change, and it does not inherently make data-driven measurement difficult. It can be used for both short-term and long-term objectives depending on design. The real weakness is that a KPI may oversimplify performance by emphasizing what can be counted rather than everything that matters. Therefore, the correct answer is that it only accounts for quantitative measures.
質問 # 107
What are two benefits of good data quality management in improving business decision-making?
Choose 2 answers.
正解：A、B
解説：
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.
質問 # 108
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?
正解：C
解説：
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.
質問 # 109
A normally distributed data index of vehicle safety ratings has a mean of 100 and a standard deviation of 15.
What is the probability that a randomly selected vehicle safety score from the data set will be between 85 and
115?
正解：D
解説：
The interval from 85 to 115 is exactly one standard deviation below and above the mean, since the mean is
100 and the standard deviation is 15. In a normal distribution, the empirical rule states that approximately 68 percent of observations fall within one standard deviation of the mean, about 95 percent fall within two standard deviations, and about 99.7 percent fall within three standard deviations. Because the range 85 to 115 corresponds to mean ± 1 standard deviation, the probability of selecting a score in that range is about 68 percent. Among the available options, 68.8 percent is the correct choice and best represents this probability.
The other values correspond to wider intervals: 95.4 percent is associated with two standard deviations and
99.7 percent with three. A value of 100 percent would imply every possible score lies in that range, which is not true for a normal distribution. Therefore, the correct answer is 68.8 percent because the question describes the one-standard-deviation interval around the mean.
質問 # 110
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