WGU C207 DATA-DRIVEN DECISION MAKING OA PRACTICE
QUESTIONS, VERIFIED ANSWERS & RATIONALES 100%
CORRECT!(Correlation vs Causation)
Question 1 (Multiple Choice)
A city transit authority observes a strong positive correlation between the daily volume
of ice cream sales at station kiosks and the number of reported pickpocketing incidents
on the subway trains. The transit board wants to launch a public safety campaign
restricting ice cream vendors from operating on platforms to lower crime. What
fundamental statistical error is the transit board making?
● A. Assuming that a high correlation coefficient proves a direct cause-and-effect
relationship.
● B. Committing a Type II statistical error by failing to reject a false null hypothesis.
● C. Confusing an ordinal measurement scale with a ratio scale.
● D. Failing to account for heteroscedasticity in a time-series regression model.
Correct Answer: A. Assuming that a high correlation coefficient proves a direct
cause-and-effect relationship.
Rationale: A statistical correlation simply indicates that two variables move together. In
this scenario, ambient temperature (a confounding or lurking variable) drives both ice
cream consumption and public foot traffic, creating a spurious correlation. Concluding
that ice cream causes crime violates the core rule that correlation does not equal
causation.
Question 2 (Multiple Choice)
A corporate wellness director analyzes company data and finds a strong negative
correlation between the number of hours employees spend working remotely and their
average daily coffee consumption in the office cafeteria. Management proposes forcing
all remote employees back to the office full-time under the assumption that it will
naturally increase coffee sales. Why is this logical deduction flawed?
● A. The data suffers from severe autocorrelation across consecutive days.
● B. The negative correlation does not prove that remote work status causes a
drop in cafeteria coffee consumption, as other factors (such as home-brewed
habits or schedule structures) may be responsible.
● C. A negative correlation invalidates any possibility of performing a linear
regression analysis.
● D. Coffee consumption is a nominal variable and cannot be correlated with
continuous work hours.
,Correct Answer: B. The negative correlation does not prove that remote work status
causes a drop in cafeteria coffee consumption, as other factors (such as home-brewed
habits or schedule structures) may be responsible.
Rationale: Observing a correlation in an observational dataset does not establish
directional causation. Employees working from home may simply drink coffee
purchased elsewhere or made at home, meaning remote status does not automatically
dictate their consumption behavior through a direct causal mechanism.
Question 3 (Multiple Choice)
An educational analyst notes a high positive correlation between the number of books
present in a child's home and their standardized reading comprehension test scores.
The school district launches an initiative to mail 50 free books to every low-achieving
student's home, expecting test scores to rise automatically. Which analytical pitfall best
describes this strategy?
● A. Assuming that increasing book inventory alone guarantees improved cognitive
comprehension without accounting for confounding socioeconomic factors.
● B. Relying on a Chi-square test of independence instead of a paired t-test.
● C. Violating the assumption of homoscedasticity.
● D. Confusing nominal data categories with interval scaling.
Correct Answer: A. Assuming that increasing book inventory alone guarantees
improved cognitive comprehension without accounting for confounding socioeconomic
factors.
Rationale: While book ownership correlates with higher scores, the number of books is
often a proxy for broader socioeconomic status, parental engagement, and educational
support (lurking variables). Simply shipping physical books does not inherently alter the
underlying causal drivers of academic performance.
Question 4 (Multiple Choice)
A fitness tracker manufacturer publishes a study showing that users who manually log
their workouts at least five times a week have a significantly lower body mass index
(BMI) than those who do not. The marketing team claims that "logging workouts with our
app causes rapid weight loss." What is the primary flaw in this marketing claim?
● A. The study failed to use a randomized controlled experiment, meaning
self-selection bias (highly motivated individuals naturally log workouts and
maintain better diets) could be the true causal driver.
● B. BMI is an ordinal scale and cannot be used in correlation calculations.
, ● C. The sample size is automatically invalid if it is under 30 observations.
● D. The company committed a Type I error by rejecting a true null hypothesis.
Correct Answer: A. The study failed to use a randomized controlled experiment,
meaning self-selection bias (highly motivated individuals naturally log workouts and
maintain better diets) could be the true causal driver.
Rationale: Observational data is prone to selection bias. People who choose to log
workouts are often already health-conscious. The app's logging feature itself may not be
the direct causal mechanism driving weight loss; rather, the underlying personal
motivation causes both behaviors.
Question 5 (Multiple Choice)
A real estate analyst discovers a strong positive correlation between the number of
luxury cars parked outside suburban homes and the average local high school
graduation rate. The local municipality considers subsidizing luxury car leases for
families in lower-performing districts to boost graduation rates. What core analytical
concept does this plan misunderstand?
● A. Autocorrelation in time-series data.
● B. Spurious correlation driven by a lurking variable (wealth/neighborhood
affluence) rather than a direct causal link.
● C. The difference between a one-tailed and two-tailed hypothesis test.
● D. The application of process capability indices ($C_{pk}$).
Correct Answer: B. Spurious correlation driven by a lurking variable
(wealth/neighborhood affluence) rather than a direct causal link.
Rationale: Neighborhood affluence (wealth) is a classic confounding variable that
causes both high rates of luxury car purchases and well-funded, high-performing local
schools. Luxury cars do not cause students to graduate; wealth facilitates both.
Question 6 (Multiple Choice)
An operations manager at a shipping facility notices a strong correlation between the
frequency of equipment maintenance checks and the total number of recorded
machinery breakdowns per month. Surprised, the manager suggests stopping
maintenance checks to reduce breakdowns. What is the critical error in the manager's
logic?
● A. Reverse causality / misunderstanding the direction of the relationship, as
frequent breakdowns often prompt more emergency maintenance checks rather
than maintenance checks causing the breakdowns.
QUESTIONS, VERIFIED ANSWERS & RATIONALES 100%
CORRECT!(Correlation vs Causation)
Question 1 (Multiple Choice)
A city transit authority observes a strong positive correlation between the daily volume
of ice cream sales at station kiosks and the number of reported pickpocketing incidents
on the subway trains. The transit board wants to launch a public safety campaign
restricting ice cream vendors from operating on platforms to lower crime. What
fundamental statistical error is the transit board making?
● A. Assuming that a high correlation coefficient proves a direct cause-and-effect
relationship.
● B. Committing a Type II statistical error by failing to reject a false null hypothesis.
● C. Confusing an ordinal measurement scale with a ratio scale.
● D. Failing to account for heteroscedasticity in a time-series regression model.
Correct Answer: A. Assuming that a high correlation coefficient proves a direct
cause-and-effect relationship.
Rationale: A statistical correlation simply indicates that two variables move together. In
this scenario, ambient temperature (a confounding or lurking variable) drives both ice
cream consumption and public foot traffic, creating a spurious correlation. Concluding
that ice cream causes crime violates the core rule that correlation does not equal
causation.
Question 2 (Multiple Choice)
A corporate wellness director analyzes company data and finds a strong negative
correlation between the number of hours employees spend working remotely and their
average daily coffee consumption in the office cafeteria. Management proposes forcing
all remote employees back to the office full-time under the assumption that it will
naturally increase coffee sales. Why is this logical deduction flawed?
● A. The data suffers from severe autocorrelation across consecutive days.
● B. The negative correlation does not prove that remote work status causes a
drop in cafeteria coffee consumption, as other factors (such as home-brewed
habits or schedule structures) may be responsible.
● C. A negative correlation invalidates any possibility of performing a linear
regression analysis.
● D. Coffee consumption is a nominal variable and cannot be correlated with
continuous work hours.
,Correct Answer: B. The negative correlation does not prove that remote work status
causes a drop in cafeteria coffee consumption, as other factors (such as home-brewed
habits or schedule structures) may be responsible.
Rationale: Observing a correlation in an observational dataset does not establish
directional causation. Employees working from home may simply drink coffee
purchased elsewhere or made at home, meaning remote status does not automatically
dictate their consumption behavior through a direct causal mechanism.
Question 3 (Multiple Choice)
An educational analyst notes a high positive correlation between the number of books
present in a child's home and their standardized reading comprehension test scores.
The school district launches an initiative to mail 50 free books to every low-achieving
student's home, expecting test scores to rise automatically. Which analytical pitfall best
describes this strategy?
● A. Assuming that increasing book inventory alone guarantees improved cognitive
comprehension without accounting for confounding socioeconomic factors.
● B. Relying on a Chi-square test of independence instead of a paired t-test.
● C. Violating the assumption of homoscedasticity.
● D. Confusing nominal data categories with interval scaling.
Correct Answer: A. Assuming that increasing book inventory alone guarantees
improved cognitive comprehension without accounting for confounding socioeconomic
factors.
Rationale: While book ownership correlates with higher scores, the number of books is
often a proxy for broader socioeconomic status, parental engagement, and educational
support (lurking variables). Simply shipping physical books does not inherently alter the
underlying causal drivers of academic performance.
Question 4 (Multiple Choice)
A fitness tracker manufacturer publishes a study showing that users who manually log
their workouts at least five times a week have a significantly lower body mass index
(BMI) than those who do not. The marketing team claims that "logging workouts with our
app causes rapid weight loss." What is the primary flaw in this marketing claim?
● A. The study failed to use a randomized controlled experiment, meaning
self-selection bias (highly motivated individuals naturally log workouts and
maintain better diets) could be the true causal driver.
● B. BMI is an ordinal scale and cannot be used in correlation calculations.
, ● C. The sample size is automatically invalid if it is under 30 observations.
● D. The company committed a Type I error by rejecting a true null hypothesis.
Correct Answer: A. The study failed to use a randomized controlled experiment,
meaning self-selection bias (highly motivated individuals naturally log workouts and
maintain better diets) could be the true causal driver.
Rationale: Observational data is prone to selection bias. People who choose to log
workouts are often already health-conscious. The app's logging feature itself may not be
the direct causal mechanism driving weight loss; rather, the underlying personal
motivation causes both behaviors.
Question 5 (Multiple Choice)
A real estate analyst discovers a strong positive correlation between the number of
luxury cars parked outside suburban homes and the average local high school
graduation rate. The local municipality considers subsidizing luxury car leases for
families in lower-performing districts to boost graduation rates. What core analytical
concept does this plan misunderstand?
● A. Autocorrelation in time-series data.
● B. Spurious correlation driven by a lurking variable (wealth/neighborhood
affluence) rather than a direct causal link.
● C. The difference between a one-tailed and two-tailed hypothesis test.
● D. The application of process capability indices ($C_{pk}$).
Correct Answer: B. Spurious correlation driven by a lurking variable
(wealth/neighborhood affluence) rather than a direct causal link.
Rationale: Neighborhood affluence (wealth) is a classic confounding variable that
causes both high rates of luxury car purchases and well-funded, high-performing local
schools. Luxury cars do not cause students to graduate; wealth facilitates both.
Question 6 (Multiple Choice)
An operations manager at a shipping facility notices a strong correlation between the
frequency of equipment maintenance checks and the total number of recorded
machinery breakdowns per month. Surprised, the manager suggests stopping
maintenance checks to reduce breakdowns. What is the critical error in the manager's
logic?
● A. Reverse causality / misunderstanding the direction of the relationship, as
frequent breakdowns often prompt more emergency maintenance checks rather
than maintenance checks causing the breakdowns.
