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| Section | Objectives |
|---|---|
| Data Fundamentals and Business Analytics | - Descriptive statistics (mean, median, variance, standard deviation) - Data types and data collection methods |
| Hypothesis Testing | - Null and alternative hypotheses - t-tests, chi-square tests, and significance testing |
| Decision Making Models | - Risk and uncertainty in decision-making - Decision trees and expected value analysis |
| Probability and Statistical Inference | - Probability concepts and distributions - Sampling methods and sampling error |
| Regression and Correlation Analysis | - Interpreting correlation and causation - Linear regression modeling |
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NEW QUESTION # 68
A financial analyst theorizes that commute times increase as the percentage of land availability for homes in a city decreases. To test this theory, the analyst uses a regression analysis. Which analysis result is supportive of this analyst's theory?
Answer: A
Explanation:
A regression result is most supportive of a theory when it shows a strong relationship between the independent and dependent variables. In this case, the analyst believes that commute times rise as land availability for homes falls. Among the answer choices, an R-squared value of 0.90 provides the strongest support because it indicates that about 90 percent of the variation in commute times is explained by the regression model. This suggests a very strong model fit. By contrast, an R-squared value of 0.10 would indicate a weak explanatory relationship. The p-values of 0.50 and 1 do not support the theory because large p- values suggest that the regression coefficient is not statistically significant. In regression analysis, a low p- value typically supports the idea that the predictor variable has a meaningful relationship with the outcome variable. Since no low p-value is offered, the best supportive result among the choices is the high R-squared value. Therefore, the correct answer is 0.90 because it indicates the model strongly explains the observed pattern.
NEW QUESTION # 69
What is a statistical process control procedure for a drill manufacturer?
Answer: A
Explanation:
Statistical process control (SPC)focuses on monitoring production processes to ensure they remain within acceptable limits. In data-driven decision making, SPC uses control charts and statistical measures to detect variation and identify whether a process is operating as intended.
For a drill manufacturer, determining whether theweight of selected drills is within a tolerable rangeis a classic SPC activity. Consistent weight indicates stable materials and manufacturing processes, while deviations may signal defects or process drift.
Market segmentation and demand forecasting are strategic analytics tasks, not process control activities.
Collaborative planning forecasting and replenishment relates to supply chain coordination rather than manufacturing quality control.
Therefore, the correct answer isB, as SPC is concerned with maintaining process consistency and product quality.
NEW QUESTION # 70
What is a disadvantage of a key performance indicator (KPI)?
Answer: A
Explanation:
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.
NEW QUESTION # 71
According to quality management principles, which two continuous improvement commitments should every individual in an organization make?
Choose 2 answers.
Answer: B,C
Explanation:
Quality management emphasizescontinuous improvement at the individual levelas a foundation for organizational excellence. In data-driven decision making, this involves a commitment by every individual to enhance both theirskillsandeffectivenessover time.
Increasing one's skills ensures that employees remain competent, adaptable, and capable of using analytical tools and data effectively. Improving effectiveness focuses on applying those skills efficiently to produce better outcomes, reduce errors, and add value to organizational processes.
Independent work processes and expert-level objectives are not universal expectations for all employees and may not align with collaborative quality frameworks. Continuous improvement is incremental and inclusive, encouraging consistent growth rather than elite specialization.
Therefore, the correct answers areA and B.
NEW QUESTION # 72
A financial analyst theorizes that commute times increase as the percentage of land availability for homes in a city decreases. To test this hypothesis, the analyst uses a regression analysis to explore how land availability predicts commute time.
What does land availability represent in this regression?
Answer: D
Explanation:
In regression analysis, theindependent variableis the predictor used to explain or estimate changes in another variable. In data-driven decision making, identifying the correct variable roles is essential for meaningful interpretation.
In this scenario, land availability is used to predict commute time. Commute time is the outcome being explained, making it the dependent or target variable. Land availability influences or explains changes in commute time, which makes it theindependent variable.
Controls are additional variables included to isolate effects, but land availability is the primary predictor of interest. Therefore, optionCis correct.
NEW QUESTION # 73
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