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| Section | Objectives |
|---|---|
| Topic 1: Business Intelligence and Analytics | - Predictive Analytics Basics - Data Mining Concepts - Dashboards and Reporting - Key Performance Indicators (KPIs) |
| Topic 2: Data Analysis Fundamentals | - Data Types and Measurement Scales - Descriptive Statistics - Data Quality and Cleaning - Data Visualization Techniques |
| Topic 3: Data-Driven Culture and Communication | - Building Data-Informed Organizations - Presenting Data Insights - Ethical Considerations in Data Use - Stakeholder Communication |
| Topic 4: Decision-Making Frameworks | - Rational Decision Models - Cost-Benefit Analysis - Evidence-Based Decision Making - Risk Analysis and Assessment |
>> Latest Data-Driven-Decision-Making Exam Questions <<
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NEW QUESTION # 86
Which performance metric simultaneously accounts for financial, customer, internal process, and learning metrics?
Answer: B
Explanation:
The balanced scorecard is the performance framework that simultaneously accounts for financial, customer, internal process, and learning and growth metrics. It was developed to provide a more complete view of organizational performance than financial measures alone. By incorporating these four perspectives, organizations can connect day-to-day activities with long-term strategy and ensure that performance is evaluated in a balanced way. Financial measures show economic results, customer measures reflect market and service outcomes, internal process measures track operational efficiency and quality, and learning metrics focus on improvement, capability development, and organizational growth. A customer complaint report addresses only one narrow area. A balance sheet and an income statement are financial documents and do not capture the full multidimensional view described in the question. Because the question asks for the metric that integrates all four of these important performance areas, the correct answer is balanced scorecard.
NEW QUESTION # 87
What is true about outliers?
Choose 2 answers.
Answer: A,D
Explanation:
Outliers are observations that differ substantially from the rest of the data, but they are not automatically errors and should not be removed without investigation. One correct statement is that miskeyed outliers can be corrected before analysis. For example, if a value of 500 is entered instead of 50, this is a data-entry error, not a meaningful observation, and it should be fixed using source verification. Another correct statement is that outliers can help determine whether something does not belong in the study. They may reveal invalid records, unusual conditions, a different population, process breakdowns, or rare but important events. The incorrect choices are too absolute. Not all outliers are statistically significant, even under a normal distribution, because significance depends on context, sample size, and method. Likewise, not all observed outliers should be eliminated. Some outliers contain valuable information and can indicate real variation that deserves attention. In quality control, fraud detection, medical screening, and operational monitoring, outliers may be among the most important data points. Therefore, the correct answers are the ones that recognize both correction of miskeyed values and the analytical value of identifying unusual observations.
NEW QUESTION # 88
How should Ishikawa's seven basic tools of quality be used?
Choose 2 answers.
Answer: A,C
Explanation:
Ishikawa's seven basic tools of quality are designed to support practical problem-solving and continuous improvement across all levels of an organization. These tools are most effective when used in combination and when the output from one tool serves as the input for another. For example, a check sheet can be used to collect defect data, which can then be summarized in a Pareto chart, and the findings may later be explored further with a cause-and-effect diagram. This interconnected use is one of the reasons the tools are so widely valued in quality management. The statement that the tools should only be used by high-level managers is incorrect because one of their strengths is accessibility; they are intended to be understandable and usable by ordinary workers as well as supervisors and analysts. The statement about recognizing trends within only one graph is also too restrictive and does not describe the broader practical use of the tools. Therefore, the correct answers are that the output from one tool can become another tool's input and that the tools can be used together.
NEW QUESTION # 89
Two vendors sell a dozen raw materials that a company needs to build its products. Which type of analysis should be used to determine if one of the vendors has a better average price at a given point in time?
Answer: A
Explanation:
To determine whether one vendor has a better average price than another, the company should use data analysis. This is the broad analytical approach that involves collecting pricing information, organizing the values, comparing averages, and possibly applying additional statistical methods to evaluate the difference.
The task is numerical and evidence-based, making data analysis the correct and most complete choice.
Heuristic analysis usually refers to rule-of-thumb decision methods rather than direct statistical comparison.
Background analysis is not the standard term for comparing measurable pricing information. Graphical analysis may help visualize price differences, but graphs alone do not fully describe the method needed to determine average pricing performance. Because the question asks which type of analysis should be used to compare average price, the answer is the one that directly refers to analyzing the numerical data itself.
Therefore, the correct answer is data analysis.
NEW QUESTION # 90
Amusement Park W is in California. Amusement Park X is in Texas. A survey asks 1,000 people living in California if they prefer Amusement Park W or X.
Which problem exists with this survey?
Answer: D
Explanation:
The primary problem with this survey issystematic error, which occurs when the data collection process consistently favors certain outcomes due to flawed design. In data-driven decision making, systematic error arises when a sampling method introduces bias that skews results in a predictable direction.
In this scenario, surveying only people living in California creates a location-based bias. Respondents are far more likely to prefer Amusement Park W because it is geographically closer, more familiar, and more accessible than Amusement Park X in Texas. This bias does not occur randomly; instead, it systematically influences responses toward one option, making the results unreliable for comparing overall preferences between the two parks.
Random error would involve unpredictable variation, which is not the issue here. Measurement bias relates to how questions are asked or measured, and information bias concerns inaccurate or misleading data reporting.
The core issue is thenon-representative sample, which violates the principle of unbiased data collection.
Data-driven decision making emphasizes that valid conclusions require representative samples. Because the survey design inherently favors one outcome, the results cannot be generalized, makingsystematic errorthe correct answer.
NEW QUESTION # 91
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