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| Section | Objectives |
|---|---|
| Topic 1: Decision-Making Frameworks | - Rational Decision Models - Cost-Benefit Analysis - Risk Analysis and Assessment - Evidence-Based Decision Making |
| Topic 2: Data-Driven Culture and Communication | - Ethical Considerations in Data Use - Building Data-Informed Organizations - Presenting Data Insights - Stakeholder Communication |
| Topic 3: Business Intelligence and Analytics | - Predictive Analytics Basics - Data Mining Concepts - Dashboards and Reporting - Key Performance Indicators (KPIs) |
| Topic 4: Data Analysis Fundamentals | - Data Quality and Cleaning - Data Types and Measurement Scales - Data Visualization Techniques - Descriptive Statistics |
>> Data-Driven-Decision-Making Latest Test Answers <<
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NEW QUESTION # 79
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: C
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 # 80
Which two characteristics must a researcher consider concerning data quality when ensuring that an analysis is based on a clean data set?
Choose 2 answers.
Answer: C,D
Explanation:
When evaluating whether a data set is clean enough for analysis, a researcher must focus on data quality dimensions that directly affect validity and usefulness. Two important characteristics are uniqueness and relevance. Data elements must be unique to prevent duplicate records from distorting counts, averages, totals, and trend analyses. Duplicate entries can lead to biased results, especially in customer, transaction, or survey data. Relevance is equally important because even accurate data are not helpful if they do not pertain to the question being studied. A clean data set should support the actual purpose of the analysis rather than merely being complete or large. The statement about age is incorrect because timeliness often matters; outdated data may no longer reflect the current environment. The statement that data cannot contain outliers is also too absolute. Outliers may be valid observations and can sometimes reveal important conditions, anomalies, or data-entry problems that require investigation rather than automatic removal. Thus, the best two characteristics are uniqueness and relevance, because both directly support meaningful, accurate, and decision- ready analysis.
NEW QUESTION # 81
Which process is considered a statistical process control activity?
Answer: A
Explanation:
Statistical process control involves using statistical methods to monitor, control, and improve production processes. A central purpose of this approach is to determine whether a process is operating within acceptable variation limits. Therefore, determining if the precision of a manufactured product is within a tolerable range is a direct example of statistical process control. This type of activity uses measured data to evaluate consistency, detect abnormal variation, and maintain quality standards. Evaluating consumer complaints may provide useful quality feedback, but it is not the direct statistical monitoring activity described by process control methods. Aligning marketing strategy with manufacturing capabilities is a business planning issue rather than a process control task. Forecasting future consumer demand is a forecasting and analytics activity, not statistical process control. The defining feature of statistical process control is monitoring production behavior using measurable process data and tolerance limits. Therefore, the correct answer is the option that focuses on determining whether the manufactured product's precision remains within an acceptable range.
NEW QUESTION # 82
What classifies analytics as descriptive, predictive, or prescriptive?
Answer: D
Explanation:
Analytics is classified as descriptive, predictive, or prescriptive based onthe purpose of the analysis and the methods used to carry it out, which is a foundational concept in data-driven decision making. The distinction reflects the type of managerial question being addressed rather than technical aspects such as software tools, sample size, or data reliability.
Descriptive analytics focuses on understandingwhat has happenedby summarizing historical data. It relies on descriptive statistics, reports, dashboards, and data visualizations to provide insights into past performance.
Predictive analytics extends this approach to determinewhat is likely to happenby using statistical models, probability distributions, regression analysis, and forecasting techniques to estimate future outcomes.
Prescriptive analytics goes further by identifyingwhat should be doneto achieve desired results. It uses optimization models, decision trees, simulations, and scenario analysis to recommend the best course of action under given constraints.
In data-driven decision making, the classification of analytics depends on how results are intended to support decisions and the analytical techniques applied to achieve that goal. Factors such as data quality and software influence accuracy and efficiency but do not define the analytics category itself. Therefore, the correct classification criterion is thepurpose and methods, making optionCthe correct answer.
NEW QUESTION # 83
How do a run chart and a control chart differ?
Answer: A
Explanation:
A run chart and a control chart are similar in that both display data over time, making it possible to observe trends, shifts, or recurring patterns in a process. The key difference is that a control chart includes control limits, or constraints, that define the expected range of normal variation for the process. These limits help analysts determine whether the process is statistically stable or whether unusual variation may signal a problem that requires attention. A run chart does not include those control boundaries; it simply displays the values in time order. Because of this, the correct description is that the two charts are essentially the same in structure, except a control chart includes limits or constraints that a process should not exceed. The options that describe one as a snapshot in time are incorrect because both are time-based charts. Therefore, the correct answer is the option identifying the control chart as the version that adds limits or thresholds for process monitoring.
NEW QUESTION # 84
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