WGU C207 DATA-DRIVEN
DECISION- MAKIN
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
,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. Reliability ensures consistency, but
validity ensures that the measurement truly represents what it is intended to
measure. Multiple researchers in different locations should be able to achieve similar
results to confirm validity.
7. If you were to take your temperature 10 times in a row using the same
thermometer and got the same result every time, you could say that the thermometer
is:
A) Accurate
B) Reliable
C) Invalid
D) Biased
Answer: B) Reliable
Rationale: Reliability refers to consistency in measurement. Even if the thermometer
consistently gives the same reading, it may not reflect the true temperature
(accuracy). Repeatable results demonstrate reliability but not necessarily validity.
8. According to the 2000 census, the average number of people in a family in the U.S.
was 3.17. Since it isn't possible to have .17 of a person, you would use a data point to
describe the number of people in your family:
A) Continuous
B) Discrete
C) Ordinal
D) Nominal
Answer: B) Discrete
Rationale: Discrete data can only take distinct, separate values, such as whole
, numbers of people. Continuous data, by contrast, can take any value within a range.
The number of family members is countable and cannot include fractions of
individuals.
9. You survey 100 New Yorkers about their preference for New York-style or Chicago-
style pizza. What would be wrong with this?
A) Sampling bias
B) Measurement bias
C) Data entry error
D) Systematic error
Answer: B) Measurement bias
Rationale: Asking only New Yorkers creates a bias because their responses are not
representative of the overall population, producing measurement bias. Surveying a
skewed demographic may result in over- or under-representing certain preferences. A
representative sample is required for accurate measurement.
10. Rankings are an example of which kind of data?
A) Nominal
B) Ordinal
C) Discrete
D) Continuous
Answer: B) Ordinal
Rationale: Ordinal data involves order or ranking but does not specify the magnitude
of differences between ranks. For example, first, second, and third place show order
but not exact
differences in performance. Understanding the type of data is critical for selecting appropriat
y y y y y y y y y y y y
e statistical methods.
y y
DECISION- MAKIN
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
,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. Reliability ensures consistency, but
validity ensures that the measurement truly represents what it is intended to
measure. Multiple researchers in different locations should be able to achieve similar
results to confirm validity.
7. If you were to take your temperature 10 times in a row using the same
thermometer and got the same result every time, you could say that the thermometer
is:
A) Accurate
B) Reliable
C) Invalid
D) Biased
Answer: B) Reliable
Rationale: Reliability refers to consistency in measurement. Even if the thermometer
consistently gives the same reading, it may not reflect the true temperature
(accuracy). Repeatable results demonstrate reliability but not necessarily validity.
8. According to the 2000 census, the average number of people in a family in the U.S.
was 3.17. Since it isn't possible to have .17 of a person, you would use a data point to
describe the number of people in your family:
A) Continuous
B) Discrete
C) Ordinal
D) Nominal
Answer: B) Discrete
Rationale: Discrete data can only take distinct, separate values, such as whole
, numbers of people. Continuous data, by contrast, can take any value within a range.
The number of family members is countable and cannot include fractions of
individuals.
9. You survey 100 New Yorkers about their preference for New York-style or Chicago-
style pizza. What would be wrong with this?
A) Sampling bias
B) Measurement bias
C) Data entry error
D) Systematic error
Answer: B) Measurement bias
Rationale: Asking only New Yorkers creates a bias because their responses are not
representative of the overall population, producing measurement bias. Surveying a
skewed demographic may result in over- or under-representing certain preferences. A
representative sample is required for accurate measurement.
10. Rankings are an example of which kind of data?
A) Nominal
B) Ordinal
C) Discrete
D) Continuous
Answer: B) Ordinal
Rationale: Ordinal data involves order or ranking but does not specify the magnitude
of differences between ranks. For example, first, second, and third place show order
but not exact
differences in performance. Understanding the type of data is critical for selecting appropriat
y y y y y y y y y y y y
e statistical methods.
y y
