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| Section | Weight | Objectives |
|---|---|---|
| Statistical Concepts & Descriptive Analytics | 25% | - Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution |
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals |
| Predictive Analytics & Regression | 20% | - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis - Simple & multiple linear regression |
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive - Role of data in business decisions |
| Decision Models & Prescriptive Analytics | 15% | - Quality & process improvement tools - Optimization, sensitivity analysis - Decision trees, payoff matrices, expected value |
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NEW QUESTION # 107
What are two benefits of good data quality management in improving business decision-making?
Choose 2 answers.
Answer: C,D
Explanation:
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.
NEW QUESTION # 108
Why would a human resources department use both mean and median when doing a salary evaluation of a department?
Answer: C
Explanation:
Using both mean and median helps identifyoutliers, such as very high executive salaries that skew the average. A large difference between the two indicates uneven distribution.
Thus, the correct answer isC.
NEW QUESTION # 109
Which quality management principle should team members apply?
Answer: A
Explanation:
A core principle of quality management is systems thinking, which emphasizes that organizations operate as interconnected processes rather than isolated tasks. Because of this, team members should analyze all adjustments made in one part of a system that may affect other parts of the system. This approach recognizes that a change intended to improve one area can unintentionally reduce quality, efficiency, or consistency elsewhere. Effective quality management requires understanding process interactions, cause-and-effect relationships, and the broader impact of operational decisions. Option A is incorrect because quality improvement usually seeks to streamline processes rather than add unnecessary steps. Option C is also incorrect because quality management is about coordination and continuous improvement, not encouraging competition between the organization and employees. Option D does not reflect a recognized quality principle and suggests a lack of operational discipline. Therefore, the correct principle is the one that promotes analysis of interdependence within the system, making option B the best answer.
NEW QUESTION # 110
Management uses a net promoter score.
What can management determine using this performance measurement?
Answer: D
Explanation:
Thenet promoter score (NPS)measurescustomer loyaltyby assessing the likelihood that customers will recommend a company's products or services to others. In data-driven decision making, NPS is a widely used indicator of customer satisfaction and long-term growth potential.
Customers are typically asked how likely they are to recommend the organization on a numerical scale.
Responses are categorized into promoters, passives, and detractors, and the score is calculated by subtracting the percentage of detractors from the percentage of promoters.
NPS does not directly measure financial outcomes, employee performance, or quality assurance metrics.
Instead, it serves as a customer-focused indicator that reflects overall perception and loyalty.
Therefore, the correct answer isB.
NEW QUESTION # 111
Two project teams are assigned to upgrade an on-premise data warehouse to a cloud-based data lake in 13 months. The infrastructure team has five team members, while the enterprise analytics team has three team members. The enterprise analytics team cannot move into production until the infrastructure team has completed the migration.
What should be used to find the probability that the project will be completed on time?
Answer: B
Explanation:
This scenario requires the use of **conditional probability**, which applies when the likelihood of one event depends on the occurrence of another event. In data-driven decision making, conditional probability is used to model dependent events within processes, workflows, and project timelines.
In this case, the enterprise analytics team's ability to move into production is **dependent on** the infrastructure team completing the migration. Because one event cannot occur unless another event has already occurred, the probability of completing the project on time must account for this dependency.
The multiplication principle applies to independent events, Bayes' theorem updates probabilities based on new information, and combinations are used for counting outcomes, not dependency analysis. Conditional probability explicitly captures the relationship between dependent tasks.
Project risk analysis and scheduling often rely on conditional probability to assess completion likelihood when tasks are sequentially linked. Therefore, the correct answer is **C**, conditional probability.
NEW QUESTION # 112
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