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| Section | Objectives |
|---|---|
| Topic 1: Business Intelligence and Analytics | - Dashboards and Reporting - Data Mining Concepts - Predictive Analytics Basics - Key Performance Indicators (KPIs) |
| Topic 2: Data Analysis Fundamentals | - Data Visualization Techniques - Descriptive Statistics - Data Types and Measurement Scales - Data Quality and Cleaning |
| Topic 3: Data-Driven Culture and Communication | - Presenting Data Insights - Ethical Considerations in Data Use - Stakeholder Communication - Building Data-Informed Organizations |
| Topic 4: Decision-Making Frameworks | - Evidence-Based Decision Making - Cost-Benefit Analysis - Risk Analysis and Assessment - Rational Decision Models |
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NEW QUESTION # 104
A healthcare organization implements a campaign to improve patient satisfaction during recent stays. The average patient satisfaction before the campaign is M = 4.20, SD = 3.0. Six months after the new campaign, the average patient satisfaction is M = 1.5, SD = 2.0.
Which action should the hospital management team take?
Answer: D
Explanation:
Data-driven decision making requires comparing outcomes before and after an intervention to assess effectiveness. In this scenario, the mean patient satisfaction scoredeclined from 4.20 to 1.5following implementation of the campaign, indicating a substantial decrease in satisfaction.
Despite the reduced standard deviation, the large drop in the mean suggests the campaign did not achieve its intended goal and may have negatively affected patient experience. Continuing or modifying the campaign is not justified without evidence of initial improvement or external factors explaining the decline.
Management decisions must be grounded in outcome data rather than assumptions or unrelated metrics such as patient volume. Ethical and effective use of statistics requires discontinuing interventions that demonstrably worsen outcomes.
Therefore, the correct action is todiscontinue the campaign, making optionAthe correct answer.
NEW QUESTION # 105
A firm seeks to sharply reduce sales lead times to enhance sales effectiveness and productivity. Which action should the firm take to accomplish this?
Answer: B
Explanation:
To sharply reduce sales lead times, the firm should deploy a customer relationship management tool. A CRM system helps organize customer information, automate follow-up processes, track sales opportunities, streamline communication, and improve coordination across the sales cycle. By reducing manual delays and improving access to customer data, a CRM can make the sales process faster and more efficient, directly supporting stronger sales effectiveness and productivity. Increasing the research and development budget would not address sales-cycle speed. Preparing a media campaign may generate interest or leads, but it does not necessarily reduce the time required to move prospects through the sales process. Additional quality assurance measures are more relevant to process quality and defect prevention than to reducing lead times in sales operations. Because the objective is to improve the speed and efficiency of handling prospects and customers, the most targeted and practical solution is the deployment of a CRM tool. Therefore, the correct answer is to deploy a customer relationship management tool.
NEW QUESTION # 106
What must be analyzed using powerful analytic tools?
Answer: D
Explanation:
Big datamust be analyzed using powerful analytic tools due to its volume, velocity, and variety. In data- driven decision making, traditional tools are often insufficient for processing massive, complex datasets generated from digital platforms, sensors, and transactions.
Big data requires advanced computing power, specialized software, and sophisticated algorithms to extract meaningful insights. Inferential statistics and small datasets can often be handled with conventional statistical tools.
Therefore, the correct answer isC, big data.
NEW QUESTION # 107
A nonprofit organization ran a fundraiser and would like to determine the amount of a typical donation.
Which statistic is less affected by outliers and skewed data and should be used to determine the amount of a typical donation?
Answer: B
Explanation:
In data-driven decision making, themedianis the preferred measure of central tendency when data contain outliers or are skewed. Fundraising donation amounts often exhibit right-skewed distributions, where a small number of very large donations can significantly inflate the mean. Using the mean in such cases may misrepresent what a "typical" donor gives.
The median represents the middle value when donation amounts are ordered from smallest to largest. Because it depends only on position rather than magnitude, it isrobust to extreme values. This makes it especially useful for summarizing typical behavior in skewed financial data.
The mean is sensitive to outliers, the z-score measures standardized distance from the mean, and the mode identifies the most frequent value but may not reflect central tendency in continuous donation data. Therefore, the statistic that best represents a typical donation amount is themedian, making optionCcorrect.
NEW QUESTION # 108
Which type of analytics classification uses experimental design and optimization to suggest a course of action?
Answer: B
Explanation:
Prescriptive analyticsis the analytics classification that uses experimental design and optimization techniques to suggest a specific course of action. In data-driven decision making, prescriptive analytics represents the most advanced stage of analytics, as it not only predicts outcomes but also recommends decisions that lead to optimal results.
Descriptive analytics summarizes historical data to explain what has already happened, while predictive analytics uses statistical and probabilistic models to estimate what is likely to happen in the future. Diagnostic analytics focuses on understanding why something happened by identifying root causes. In contrast, prescriptive analytics answers the critical question:what should be done.
Prescriptive analytics relies on methods such as optimization models, simulation, decision trees, and experimental design. These techniques evaluate multiple scenarios, constraints, and objectives to identify the best possible action. For example, organizations use prescriptive analytics to optimize pricing, allocate resources efficiently, schedule operations, or determine optimal investment strategies.
Within data-driven decision-making frameworks, prescriptive analytics bridges analysis and action by directly supporting managerial decision-making. It transforms analytical insights into concrete recommendations that can be implemented to improve performance and outcomes. Therefore, the correct answer isC, as prescriptive analytics explicitly uses experimental design and optimization to suggest a course of action.
NEW QUESTION # 109
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