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

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

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WGU VPC2Data-Driven Decision MakingC207 Sample Questions (Q74-Q79):

NEW QUESTION # 74
Which type of study is also known as a quasi-experimental study?

Answer: D

Explanation:
A **quasi-experimental study** is commonly referred to as an **observational study** in data-driven decision making. Unlike true experiments, quasi-experimental studies do not involve random assignment of subjects to treatment and control groups. Instead, researchers observe outcomes in naturally occurring groups and attempt to draw conclusions about relationships between variables.
In observational studies, the researcher does not control the assignment of treatments. As a result, these studies are more susceptible to bias and confounding variables than randomized experiments. However, they are often necessary when controlled experimentation is impractical, unethical, or too costly. For example, studying the impact of policy changes or economic conditions typically relies on observational data.
Blind studies are a form of experimental design used to reduce bias, hypothesis testing is a statistical process rather than a study type, and content validity refers to measurement quality. None of these represent quasi- experimental designs.
In data-driven decision making, observational (quasi-experimental) studies are valuable for identifying associations and generating insights, but analysts must be cautious not to infer causality without proper controls. Therefore, the correct answer is **A**.
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NEW QUESTION # 75
Which two results occur when the null hypothesis is accepted using an F-test?
Choose 2 answers.

Answer: A,B

Explanation:
When the null hypothesis is accepted in anF-test, it indicates that there is no statistically significant difference between group variances or means, depending on the test design. Acceptance occurs when thetest statistic is less than the critical value, meaning the observed variation is within expected limits.
Accepting the null hypothesis implies thatno meaningful differenceexists between the samples. If the test statistic exceeded the critical value, the null hypothesis would be rejected.
Thus, the correct results areA and D.


NEW QUESTION # 76
Research data indicate 95% confidence in a study in which subjects who were shown a product advertisement exhibited brand awareness compared to a control group who did not see the advertisement.
What can be concluded from this study?

Answer: D


NEW QUESTION # 77
A car dealership sells both new and used cars. The number of new cars sold on a given day ranges from 5 to
30 while the number of used cars sold ranges from 5 to 40. The number of used cars sold is mutually exclusive to the number of new cars sold.
Which statistic would be used to compare the number of new and used car sales on any given day?

Answer: B

Explanation:
Thechi-square statisticis used to compare frequencies of categorical, mutually exclusive outcomes. In data- driven decision making, it is appropriate for analyzing differences between observed counts.
New and used car sales represent mutually exclusive categories, making chi-square the correct choice.
Therefore, the correct answer isB.


NEW QUESTION # 78
Which process is considered a statistical process control activity?

Answer: B

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 # 79
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