WGU C207 Data-Driven Decision Making | WGU C207 Study Guide & Objective
Assessment (OA) Exam Prep 2026–2027 | WGU Data-Driven Decision
Making Course Review | Quantitative Analysis, Statistics, Data Collection,
Data Quality, Descriptive Statistics, Probability, Z-Scores, Correlation,
Regression, Forecasting, Decision Trees, Linear Programming, Break-Even
Analysis, Simulation, Quality Management, PDCA, SIPOC, Statistical Process
Control, Lean & Organizational Performance | Practice Questions, Statistical
Problems, Case Studies & Detailed Rationales
Question 1: Which statistical measure is most appropriate for determining the
middle value in a dataset that contains extreme outliers?
A. Mean
B. Median
C. Mode
D. Range
CORRECT ANSWER: B. Median
Rationale: The median is resistant to extreme values because it identifies the
middle position rather than calculating an average of all values. When outliers
skew the distribution, the mean becomes distorted while the median remains
stable and representative of the typical value in the dataset.
Question 2: In the context of data-driven decision making, what distinguishes
information from raw data?
A. Information is always numerical while data is qualitative
B. Information is data that has been processed and given context
C. Data is more valuable than information for decision makers
D. Information requires less storage than raw data
CORRECT ANSWER: B. Information is data that has been processed and given
context
Rationale: Raw data consists of unorganized facts and figures. When data is
processed, organized, and contextualized, it becomes information that can
meaningfully inform decisions.
Question 3: Which analytics type focuses on predicting future outcomes based
on historical patterns?
,A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
CORRECT ANSWER: C. Predictive analytics
Rationale: Predictive analytics uses historical data and statistical models to
forecast future events or behaviors, such as equipment failures or customer
churn.
Question 4: What is the primary purpose of the Davenport-Kim three-stage
model?
A. To automate all managerial decisions
B. To frame problems, solve them, and communicate results
C. To replace statistical analysis with intuition
D. To eliminate the need for data collection
CORRECT ANSWER: B. To frame problems, solve them, and communicate results
Rationale: The Davenport-Kim model provides a structured approach to analytics:
framing the problem, solving it through analysis, and communicating findings to
stakeholders.
Question 5: A hospital administrator notices increased patient readmission
rates. What is the first step in the data-driven decision-making process?
A. Implementing a new discharge protocol immediately
B. Defining the problem and formulating specific questions
C. Collecting all available patient data
D. Consulting physicians about discharge practices
CORRECT ANSWER: B. Defining the problem and formulating specific questions
Rationale: The initial step in data-driven decision making is clearly defining the
problem and formulating specific, answerable questions that will guide
subsequent data collection and analysis.
Question 6: Which level of measurement is represented by a dataset of
temperatures measured in Fahrenheit?
,A. Nominal
B. Ordinal
C. Interval
D. Ratio
CORRECT ANSWER: C. Interval
Rationale: Interval data has ordered values with equal intervals between points,
but lacks a true zero point. Fahrenheit temperature is a classic example because
zero degrees does not indicate the absence of temperature.
Question 7: What distinguishes ratio data from interval data?
A. Ratio data has a natural zero point
B. Ratio data cannot be ordered
C. Ratio data uses categories exclusively
D. Ratio data has unequal intervals
CORRECT ANSWER: A. Ratio data has a natural zero point
Rationale: Ratio data possesses all properties of interval data plus a meaningful
zero point that represents the absence of the measured quality, such as height or
weight.
Question 8: A manufacturing company uses sensor data to predict equipment
maintenance needs. This exemplifies which analytics category?
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
CORRECT ANSWER: C. Predictive analytics
Rationale: Predictive analytics analyzes historical data to forecast future events.
Using sensor data to anticipate maintenance needs before failure occurs is a
predictive application.
Question 9: What are the three defining characteristics of big data?
A. Volume, velocity, and variety
B. Structure, storage, and security
, C. Accuracy, availability, and access
D. Collection, cleaning, and cataloging
CORRECT ANSWER: A. Volume, velocity, and variety
Rationale: Big data is characterized by its massive volume, rapid velocity of
generation, and variety of formats, which together make traditional processing
tools insufficient.
Question 10: Which quality tool is best suited for identifying the most significant
causes of a problem?
A. Flowchart
B. Pareto chart
C. Control chart
D. Scatter diagram
CORRECT ANSWER: B. Pareto chart
Rationale: Pareto charts apply the 80/20 principle by displaying causes in
descending order of frequency, helping organizations prioritize the few causes
that produce most problems.
Question 11: What does a SIPOC diagram accomplish?
A. It tracks financial performance metrics
B. It provides a holistic view of a process
C. It measures customer satisfaction scores
D. It logs production errors
CORRECT ANSWER: B. It provides a holistic view of a process
Rationale: SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagrams
visualize the complete workflow, helping teams understand process boundaries
and relationships.
Question 12: Which term describes data that can only take whole values with
clear boundaries?
A. Continuous data
B. Discrete data
Assessment (OA) Exam Prep 2026–2027 | WGU Data-Driven Decision
Making Course Review | Quantitative Analysis, Statistics, Data Collection,
Data Quality, Descriptive Statistics, Probability, Z-Scores, Correlation,
Regression, Forecasting, Decision Trees, Linear Programming, Break-Even
Analysis, Simulation, Quality Management, PDCA, SIPOC, Statistical Process
Control, Lean & Organizational Performance | Practice Questions, Statistical
Problems, Case Studies & Detailed Rationales
Question 1: Which statistical measure is most appropriate for determining the
middle value in a dataset that contains extreme outliers?
A. Mean
B. Median
C. Mode
D. Range
CORRECT ANSWER: B. Median
Rationale: The median is resistant to extreme values because it identifies the
middle position rather than calculating an average of all values. When outliers
skew the distribution, the mean becomes distorted while the median remains
stable and representative of the typical value in the dataset.
Question 2: In the context of data-driven decision making, what distinguishes
information from raw data?
A. Information is always numerical while data is qualitative
B. Information is data that has been processed and given context
C. Data is more valuable than information for decision makers
D. Information requires less storage than raw data
CORRECT ANSWER: B. Information is data that has been processed and given
context
Rationale: Raw data consists of unorganized facts and figures. When data is
processed, organized, and contextualized, it becomes information that can
meaningfully inform decisions.
Question 3: Which analytics type focuses on predicting future outcomes based
on historical patterns?
,A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
CORRECT ANSWER: C. Predictive analytics
Rationale: Predictive analytics uses historical data and statistical models to
forecast future events or behaviors, such as equipment failures or customer
churn.
Question 4: What is the primary purpose of the Davenport-Kim three-stage
model?
A. To automate all managerial decisions
B. To frame problems, solve them, and communicate results
C. To replace statistical analysis with intuition
D. To eliminate the need for data collection
CORRECT ANSWER: B. To frame problems, solve them, and communicate results
Rationale: The Davenport-Kim model provides a structured approach to analytics:
framing the problem, solving it through analysis, and communicating findings to
stakeholders.
Question 5: A hospital administrator notices increased patient readmission
rates. What is the first step in the data-driven decision-making process?
A. Implementing a new discharge protocol immediately
B. Defining the problem and formulating specific questions
C. Collecting all available patient data
D. Consulting physicians about discharge practices
CORRECT ANSWER: B. Defining the problem and formulating specific questions
Rationale: The initial step in data-driven decision making is clearly defining the
problem and formulating specific, answerable questions that will guide
subsequent data collection and analysis.
Question 6: Which level of measurement is represented by a dataset of
temperatures measured in Fahrenheit?
,A. Nominal
B. Ordinal
C. Interval
D. Ratio
CORRECT ANSWER: C. Interval
Rationale: Interval data has ordered values with equal intervals between points,
but lacks a true zero point. Fahrenheit temperature is a classic example because
zero degrees does not indicate the absence of temperature.
Question 7: What distinguishes ratio data from interval data?
A. Ratio data has a natural zero point
B. Ratio data cannot be ordered
C. Ratio data uses categories exclusively
D. Ratio data has unequal intervals
CORRECT ANSWER: A. Ratio data has a natural zero point
Rationale: Ratio data possesses all properties of interval data plus a meaningful
zero point that represents the absence of the measured quality, such as height or
weight.
Question 8: A manufacturing company uses sensor data to predict equipment
maintenance needs. This exemplifies which analytics category?
A. Descriptive analytics
B. Diagnostic analytics
C. Predictive analytics
D. Prescriptive analytics
CORRECT ANSWER: C. Predictive analytics
Rationale: Predictive analytics analyzes historical data to forecast future events.
Using sensor data to anticipate maintenance needs before failure occurs is a
predictive application.
Question 9: What are the three defining characteristics of big data?
A. Volume, velocity, and variety
B. Structure, storage, and security
, C. Accuracy, availability, and access
D. Collection, cleaning, and cataloging
CORRECT ANSWER: A. Volume, velocity, and variety
Rationale: Big data is characterized by its massive volume, rapid velocity of
generation, and variety of formats, which together make traditional processing
tools insufficient.
Question 10: Which quality tool is best suited for identifying the most significant
causes of a problem?
A. Flowchart
B. Pareto chart
C. Control chart
D. Scatter diagram
CORRECT ANSWER: B. Pareto chart
Rationale: Pareto charts apply the 80/20 principle by displaying causes in
descending order of frequency, helping organizations prioritize the few causes
that produce most problems.
Question 11: What does a SIPOC diagram accomplish?
A. It tracks financial performance metrics
B. It provides a holistic view of a process
C. It measures customer satisfaction scores
D. It logs production errors
CORRECT ANSWER: B. It provides a holistic view of a process
Rationale: SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagrams
visualize the complete workflow, helping teams understand process boundaries
and relationships.
Question 12: Which term describes data that can only take whole values with
clear boundaries?
A. Continuous data
B. Discrete data
