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DATA DRIVEN DECISION MAKING (WGU C207) FINAL EXAM QUESTIONS AND VERIFIED ANSWERS PERCENT GUARANTEE PASS

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This Data Driven Decision Making (WGU C207) Final Exam Questions and Answers resource is designed to help students understand core concepts in data analytics and business decision-making. It includes key topics such as data mining limitations, growth of raw data in modern systems, and structured decision-making frameworks like the Davenport-Kim model. Each question is paired with clear answers and explanations to support deeper understanding. This study guide is ideal for WGU students preparing for the C207 final exam or revising data analysis principles. It strengthens knowledge of how data is collected, interpreted, and applied in business environments. The resource also helps learners develop critical thinking skills when evaluating trends, correlations, and decision-making processes in real-world scenarios.

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WGU C207 DATA-DRIVEN DECISION-
MAKING FINAL EXAM (2026-2027 )
QUESTIONS AND VERIFIED ANSWERS,
100% GUARANTEE PASS
1. True or False?
From data mining, someone is able to make conclusions about the underlying causes
of certain variables.

Answer: False
Rationale: Data mining identifies patterns, correlations, or trends in large datasets,
but it cannot determine causation. Without controlled experimentation, it is impossible
to know whether a variable is causing an outcome or simply associated with it.
Analysts should avoid assuming cause-and-effect from purely mined data, as
confounding factors may exist.




2. True or False?
As technology improves, there will be a greater amount of raw data.

Answer: True
Rationale: Technological advancements in sensors, IoT devices, and data collection
tools increase the volume of raw data generated. More accessible and faster data
collection methods allow organizations to gather larger datasets for analysis. This
growth also increases the importance of effective data management and analytics
techniques.




3. True or False?
The first step in the Davenport-Kim three-stage model is to frame the problem by
recognizing what the problem is and then reviewing previous findings to begin to

,structure the analysis.

,Answer: True
Rationale: Stage 1 of the Davenport-Kim model is "framing the problem." This
involves defining the problem clearly, reviewing prior research, and structuring the
analysis. Proper framing ensures that subsequent stages, including data collection and
analysis, address the correct objectives.




4. True or False?
The stage that involves the most intense statistics and data work is stage 3,
communicating results.

Answer: False
Rationale: Stage 2, "solving the problem," involves the most statistical and analytical
work. This includes data modeling, analysis, and interpretation of results. Stage 3
focuses on presenting findings and communicating insights, not performing heavy
statistical calculations.




5. True or False?
Observational studies are often used when a surveyor wants to adjust different
variables and take note of the effects.

Answer: False
Rationale: Observational studies are used when it is impractical or unethical to
control variables, unlike experimental studies where variables can be manipulated.
Observational research records naturally occurring events to identify correlations or
patterns. Causal conclusions are limited because variable manipulation does not
occur.

, 6. True or False?
Data is valid if it can be repeated by the same person in the same lab each and every
time the experiment is executed.

Answer: False
Rationale: Validity requires that data is
accurate and meaningful across different contexts, not just repeatable by one person. Relia
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bility ensures consistency, but validity ensures that the measurement truly represents what
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it is intended to measure. Multiple researchers in different locations should be able to achiev
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e similar results to confirm validity.
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7. If you were to take your temperature 10 times in a row using the same
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thermometer and got the same result every time, you could say that the thermometer is: p p p p p p p p p p p p p p p




A) Accurate p p




B) Reliable p p




C) Invalid p p




D) Biased p




Answer: B) Reliable p p p




Rationale: Reliability refers to consistency in measurement. Even if the thermometer consis
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tently gives the same reading, it may not reflect the true temperature
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(accuracy). Repeatable results demonstrate reliability but not necessarily validity.p p p p p p p p




8. According to the 2000 census, the average number of people in a family in the U.S. was 3.17.
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Since it isn't possible to have .17 of a person, you would use a data point to describe the number
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of people in your family:
p p p p p




A) Continuous p p




B) Discrete p p




C) Ordinal p p




D) Nominal p




Answer: B) Discrete p p p




Rationale: Discrete data can only take distinct, separate values, such as whole p p p p p p p p p p p p

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Institución
Data Driven Decision Making
Grado
Data Driven Decision Making

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Subido en
26 de mayo de 2026
Número de páginas
39
Escrito en
2025/2026
Tipo
Examen
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