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WGU Data-Driven-Decision-Making Exam Syllabus Topics:

SectionObjectives
Data-Driven Culture and Communication- Stakeholder Communication
- Presenting Data Insights
- Building Data-Informed Organizations
- Ethical Considerations in Data Use
Business Intelligence and Analytics- Data Mining Concepts
- Predictive Analytics Basics
- Key Performance Indicators (KPIs)
- Dashboards and Reporting
Decision-Making Frameworks- Rational Decision Models
- Risk Analysis and Assessment
- Evidence-Based Decision Making
- Cost-Benefit Analysis
Data Analysis Fundamentals- Data Quality and Cleaning
- Data Types and Measurement Scales
- Data Visualization Techniques
- Descriptive Statistics

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WGU VPC2Data-Driven Decision MakingC207 Sample Questions (Q97-Q102):

NEW QUESTION # 97
Which graphical representation depicts the steps that compose a process?

Answer: B

Explanation:
Aflowchartis the graphical tool used to depict the sequential steps that compose a process. In data-driven decision making and quality management, flowcharts visually represent how inputs move through a series of activities to produce outputs. This makes them essential for understanding, documenting, and improving processes.
Flowcharts use standardized symbols to show actions, decisions, inputs, and outputs. By mapping each step, organizations can identify inefficiencies, bottlenecks, redundancies, and opportunities for improvement. They are commonly used during process analysis, root-cause analysis, and continuous improvement initiatives.
Histograms display the distribution of numerical data, control charts monitor process variation over time, and scatterplots examine relationships between variables. None of these tools are designed to show step-by-step workflows.
Therefore, the correct answer isC, flowchart.


NEW QUESTION # 98
A sample of 1,020 people was asked how many minutes they exercise on a typical day. The data were plotted and determined to beskewed leftwith a mean of 44.75 minutes.
Which boxplot correctly graphs this data?

Answer: C


NEW QUESTION # 99
What is an appropriate management use of statistics?

Answer: D

Explanation:
An appropriate management use of statistics is **understanding the demographics of customers**, which supports informed, proactive decision-making. Data-driven decision making emphasizes using statistical analysis to explore patterns, characteristics, and trends that help organizations better understand their customers and markets.
Analyzing customer demographics such as age, income, location, and preferences allows managers to segment markets, tailor products, improve services, and allocate resources effectively. This use of statistics is descriptive and diagnostic in nature and directly supports strategic planning.
Ordering products for an entire region based on data from a single store is inappropriate due to lack of representativeness. Justifying decisions after implementation reflects misuse of statistics, as analytics should inform decisions beforehand, not rationalize them after the fact. Implementing changes solely based on survey response rate ignores the content and validity of responses.
Ethical data-driven decision making requires that statistics be used responsibly, transparently, and with appropriate context. Therefore, the correct answer is **A**, as understanding customer demographics represents a proper and effective use of statistics by management.
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NEW QUESTION # 100
A county government wants to start a cost-effective recycling program. How can the county apply data analytic approaches to attain this goal?

Answer: D

Explanation:
To create a cost-effective recycling program, the county should benchmark similar strategies used by other counties. Benchmarking is a practical data-driven approach that allows decision-makers to compare program designs, costs, participation rates, collection methods, and outcomes across jurisdictions facing similar conditions. By examining how other counties structure successful recycling initiatives, the county can identify efficient practices, realistic cost expectations, and implementation strategies that have already been tested in comparable environments. This approach is especially useful when developing a new program because it reduces trial-and-error and supports evidence-based planning. The other options are less directly related to designing and evaluating a recycling program. Analyzing county contracts or aligning funds with staffing levels may be useful in general budgeting, but they do not specifically address recycling strategy effectiveness. Audit performance research is also not closely tied to recycling program design. Therefore, the most appropriate data analytic approach is benchmarking similar strategies of other counties.


NEW QUESTION # 101
A boutique specializing in gifts reviews its sales data over the last year. It observes a slow decline in revenue in the first quarter, a growth in revenue in the second quarter, a slight decline in revenue in the third quarter, and a rapid increase in revenue in the fourth quarter.
Which data pattern type can the sales data be assessed against?

Answer: C

Explanation:
Seasonalityrefers to predictable patterns in data that repeat at regular intervals, such as quarters or months, due to seasonal factors. In data-driven decision making, identifying seasonal patterns helps organizations forecast demand and plan operations.
The boutique's revenue shows distinct quarterly patterns: declines and increases that align with different times of the year. The sharp increase in the fourth quarter is especially indicative of seasonal effects, such as holiday shopping.
Random variation and irregularity describe unpredictable fluctuations, while cyclicality refers to long-term economic cycles rather than recurring annual patterns. Therefore, the correct answer isC, seasonality.


NEW QUESTION # 102
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