WGU C207 DATA-DRIVEN DECISION-
MAKING FINAL EXAM ()
FULL PRACTICE EXAM - 80 QUESTIONS
WITH VERIFIED ANSWERS AND
RATIONALES
SECTION 1: FOUNDATIONS OF DATA & DECISION MAKING
1. A manufacturer wants to maximize their factory output while specifically minimizing labor costs.
What type of analytics might they employ to achieve this goal?
A) Descriptive Analytics
B) Predictive Analytics
C) Prescriptive Analytics
D) Diagnostic Analytics
Correct Answer: C) Prescriptive Analytics
Rationale: Prescriptive analytics is used to determine the best course of action to achieve a specific goal
(maximizing output while minimizing costs) by using optimization and simulation algorithms. Descriptive
answers "what happened?", Predictive answers "what will happen?", and Diagnostic answers "why did it
happen?"
2. For companies to attract and retain their best customers they need a complete portrait of who they
are. To develop this portrait companies turn to...
A) Statistics
B) Analytics
C) Management Science
D) Histograms
,Correct Answer: B) Analytics
Rationale: Analytics is the broad term for the discovery, analysis, and communication of meaningful
patterns in data. It encompasses the tools and processes needed to build a comprehensive customer
portrait.
3. What is the first stage of Davenport and Kim’s Three Stage Model of quantitative decision-making?
A) Solve the problem
B) Frame the problem
C) Communicate insights
D) Act on insights
Correct Answer: B) Frame the problem
Rationale: The Davenport-Kim three-stage model consists of: 1) Framing the problem, 2) Solving the
problem, and 3) Communicating results. Defining the problem's scope and objectives is the critical first
step.
4. Which of the following best describes the purpose of data-driven decision-making?
A) To replace human intuition entirely
B) To improve decisions by integrating evidence, analysis, and measurable outcomes
C) To rely exclusively on big data systems
D) To increase workload and data storage needs
Correct Answer: B) To improve decisions by integrating evidence, analysis, and measurable
outcomes
Rationale: Data-driven decision-making uses data and analysis to inform and validate decisions,
supplementing (not replacing) human judgment to achieve better, more measurable results.
5. In C207, data is defined as:
A) Personal opinions collected over time
B) Raw facts that can be transformed into meaningful information
C) Any numbers generated by a computer
D) Only information stored in enterprise databases
Correct Answer: B) Raw facts that can be transformed into meaningful information
Rationale: Data is the raw input (facts and figures). When this data is processed and organized, it
becomes information that has context and meaning.
SECTION 2: DATA TYPES, MEASUREMENT, AND ERRORS
6. The age of employees measured in years is an example of:
A) Nominal
B) Ordinal
, C) Interval
D) Ratio
Correct Answer: D) Ratio
Rationale: Ratio data has all the properties of interval data (ordered, equal intervals) but also has a true,
meaningful zero point (age 0 means no age). You can multiply and divide ratio data.
7. Customer satisfaction categorized as “Poor, Fair, Good, Excellent” is what type of variable?
A) Ratio
B) Ordinal
C) Nominal
D) Continuous
Correct Answer: B) Ordinal
Rationale: Ordinal data has a natural order or ranking (Poor < Fair < Good < Excellent), but the intervals
between the categories are not necessarily equal.
8. A zip code is an example of what type of data?
A) Ordinal
B) Interval
C) Ratio
D) Nominal
Correct Answer: D) Nominal
Rationale: Nominal data is used for labeling or categorizing variables without any quantitative value or
order. A zip code is simply a label for a geographic area; one zip code is not "greater than" another.
9. What type of data error that occurs in measurement is constant within a data set and is sometimes
caused by faulty equipment or bias?
A) Random
B) Omission
C) Outlier
D) Systematic
Correct Answer: D) Systematic
Rationale: Systematic error is a consistent, repeatable error that skews data in one direction. It is often
caused by faulty equipment, flawed calibration, or researcher bias.
10. An error that will fix itself over time as more data is collected is known as a(n):
A) Systematic Error
B) Omission Error
C) Random Error
D) Out-of-Range Error
MAKING FINAL EXAM ()
FULL PRACTICE EXAM - 80 QUESTIONS
WITH VERIFIED ANSWERS AND
RATIONALES
SECTION 1: FOUNDATIONS OF DATA & DECISION MAKING
1. A manufacturer wants to maximize their factory output while specifically minimizing labor costs.
What type of analytics might they employ to achieve this goal?
A) Descriptive Analytics
B) Predictive Analytics
C) Prescriptive Analytics
D) Diagnostic Analytics
Correct Answer: C) Prescriptive Analytics
Rationale: Prescriptive analytics is used to determine the best course of action to achieve a specific goal
(maximizing output while minimizing costs) by using optimization and simulation algorithms. Descriptive
answers "what happened?", Predictive answers "what will happen?", and Diagnostic answers "why did it
happen?"
2. For companies to attract and retain their best customers they need a complete portrait of who they
are. To develop this portrait companies turn to...
A) Statistics
B) Analytics
C) Management Science
D) Histograms
,Correct Answer: B) Analytics
Rationale: Analytics is the broad term for the discovery, analysis, and communication of meaningful
patterns in data. It encompasses the tools and processes needed to build a comprehensive customer
portrait.
3. What is the first stage of Davenport and Kim’s Three Stage Model of quantitative decision-making?
A) Solve the problem
B) Frame the problem
C) Communicate insights
D) Act on insights
Correct Answer: B) Frame the problem
Rationale: The Davenport-Kim three-stage model consists of: 1) Framing the problem, 2) Solving the
problem, and 3) Communicating results. Defining the problem's scope and objectives is the critical first
step.
4. Which of the following best describes the purpose of data-driven decision-making?
A) To replace human intuition entirely
B) To improve decisions by integrating evidence, analysis, and measurable outcomes
C) To rely exclusively on big data systems
D) To increase workload and data storage needs
Correct Answer: B) To improve decisions by integrating evidence, analysis, and measurable
outcomes
Rationale: Data-driven decision-making uses data and analysis to inform and validate decisions,
supplementing (not replacing) human judgment to achieve better, more measurable results.
5. In C207, data is defined as:
A) Personal opinions collected over time
B) Raw facts that can be transformed into meaningful information
C) Any numbers generated by a computer
D) Only information stored in enterprise databases
Correct Answer: B) Raw facts that can be transformed into meaningful information
Rationale: Data is the raw input (facts and figures). When this data is processed and organized, it
becomes information that has context and meaning.
SECTION 2: DATA TYPES, MEASUREMENT, AND ERRORS
6. The age of employees measured in years is an example of:
A) Nominal
B) Ordinal
, C) Interval
D) Ratio
Correct Answer: D) Ratio
Rationale: Ratio data has all the properties of interval data (ordered, equal intervals) but also has a true,
meaningful zero point (age 0 means no age). You can multiply and divide ratio data.
7. Customer satisfaction categorized as “Poor, Fair, Good, Excellent” is what type of variable?
A) Ratio
B) Ordinal
C) Nominal
D) Continuous
Correct Answer: B) Ordinal
Rationale: Ordinal data has a natural order or ranking (Poor < Fair < Good < Excellent), but the intervals
between the categories are not necessarily equal.
8. A zip code is an example of what type of data?
A) Ordinal
B) Interval
C) Ratio
D) Nominal
Correct Answer: D) Nominal
Rationale: Nominal data is used for labeling or categorizing variables without any quantitative value or
order. A zip code is simply a label for a geographic area; one zip code is not "greater than" another.
9. What type of data error that occurs in measurement is constant within a data set and is sometimes
caused by faulty equipment or bias?
A) Random
B) Omission
C) Outlier
D) Systematic
Correct Answer: D) Systematic
Rationale: Systematic error is a consistent, repeatable error that skews data in one direction. It is often
caused by faulty equipment, flawed calibration, or researcher bias.
10. An error that will fix itself over time as more data is collected is known as a(n):
A) Systematic Error
B) Omission Error
C) Random Error
D) Out-of-Range Error
