Making | Practice Questions, Answers & Rationales
Prepare for the WGU C207 Objective Assessment with this comprehensive study
guide featuring original practice questions, accurate answers, and detailed
rationales. Covers data-driven decision making, statistics, probability, hypothesis
testing, regression, data analysis, and business analytics concepts. Perfect for
focused review, self-assessment, and building confidence before your WGU C207
exam.
Question 1
An operations manager at a software company wants to test whether a newly
implemented coding framework has decreased the average development time for new
feature deployments. The manager collects deployment duration data from 40 specific
software modules before the change and tracks those exact same 40 modules after the
change. Which statistical test is most appropriate?
A) Simple Linear Regression
B) Chi-Square Test of Independence
C) Paired t-test
D) One-Way Analysis of Variance (ANOVA)
Rationale: A paired t-test compares the means of two related or dependent groups (the
same software modules measured "before" and "after" an operational intervention) to
see if a statistically significant difference exists.
Question 2
A regional manager tracks the monthly sales performance among four different retail
branch territories to determine if at least one layout territory is performing differently
than the others. Which statistical test should be deployed?
A) Paired t-test
B) One-Way ANOVA
C) Simple Linear Regression
D) Chi-Square Test of Independence
,Rationale: Analysis of Variance (ANOVA) is used to compare and evaluate the means
of three or more independent groups to determine if at least one group mean
significantly differs from the others.
Question 3
A marketing director compiles an annual report showing that a website's total
conversion rate increases linearly as the amount of money spent on social media
advertising increases. The correlation coefficient (r) between advertising spend and
conversion rate is calculated to be +0.88. How should this relationship be interpreted?
A) There is a weak positive linear relationship.
B) The relationship is perfect and directly causal.
C) There is a strong negative linear relationship.
D) There is a strong positive linear relationship.
Rationale: Correlation coefficients (r) range from -1.00 to +1.00. A value of +0.88
indicates a strong, positive linear relationship, meaning that as advertising spend
increases, conversion rates tend to increase significantly.
Question 4
A university data analyst uses multiple regression analysis to predict student freshman
GPA based on high school GPA, SAT scores, and hours spent in tutoring. The output
provides a Coefficient of Determination (R²) value of 0.74. What does this metric
indicate to the analyst?
A) 74% of the variance in freshman GPA is explained by the independent
variables in the model.
B) The model is incorrect 26% of the time.
C) The correlation between high school GPA and SAT scores is exactly 0.74.
D) Every unit increase in SAT score results in a 0.74 increase in freshman GPA.
Rationale: The Coefficient of Determination (R²) measures the proportion of variance in
the dependent variable (freshman GPA) that can be explained by the independent
variables in the regression model.
Question 5
,During a retail inventory audit, an analyst notes that a small group of high-end luxury
items accounts for 80% of the total inventory costs, despite making up only 20% of the
physical item volume. Which business tool or principle is this scenario demonstrating?
A) Six Sigma Black Belt Matrix
B) Pareto Principle (80/20 Rule)
C) Standard Deviation Spread
D) Linear Programming Boundary
Rationale: The Pareto Principle states that roughly 80% of consequences come from
20% of causes. In inventory and quality control, a Pareto analysis highlights the "vital
few" items or problems that demand the most attention.
Question 6
A financial analyst calculates the standard deviation of monthly returns for two different
investment portfolios over a 5-year period. Portfolio A has a standard deviation of 2.5%,
while Portfolio B has a standard deviation of 9.2%. What can the analyst conclude about
Portfolio B?
A) Portfolio B has a much lower level of volatility than Portfolio A.
B) Portfolio B has a mean return that is four times higher than Portfolio A.
C) Portfolio B has data points that are more widely spread out from its mean,
indicating higher volatility/risk.
D) Portfolio B contains exactly four times as many assets as Portfolio A.
Rationale: Standard deviation measures the spread or dispersion of a dataset relative to
its mean. A higher standard deviation indicates greater variability, which translates to
higher volatility or risk in financial contexts.
Question 7
A manufacturing plant wants to implement a systematic data-driven framework focused
on reducing defects to no more than 3.4 parts per million opportunities. Which
methodology should the organization adopt?
A) Balanced Scorecard
B) Agile Scrum Framework
C) Six Sigma
D) Porter's Five Forces
, Rationale: Six Sigma is a disciplined, data-driven quality methodology aimed at
eliminating defects in a process. Achieving Six Sigma statistical quality means a
process produces no more than 3.4 defects per million opportunities.
Question 8
An HR manager uses a scatter plot to analyze the relationship between employee years
of experience and annual salary. On the plot, all the data points trend upward from left
to right. What type of correlation does this visual anchor represent?
A) Negative Correlation
B) Zero Correlation
C) Nonlinear Curvilinear Correlation
D) Positive Correlation
Rationale: On a scatter plot, a positive correlation is visualized when data points trend
upward from left to right, indicating that as one variable increases, the other variable
also tends to increase.
Question 9
A research team is testing a new pharmaceutical drug designed to lower blood
pressure. They establish a null hypothesis (H₀) stating that the drug has no effect on
blood pressure. After analyzing the trial data, the resulting p-value is calculated to be
0.03. Assuming a standard alpha significance level (α = 0.05), what should the team
do?
A) Fail to reject the null hypothesis and conclude the drug is ineffective.
B) Reject the null hypothesis and conclude that the drug has a statistically
significant effect.
C) Change the alpha significance level to 0.01 to force a match.
D) Prove that the drug is 100% safe for all human consumption profiles.
Rationale: When the p-value is less than or equal to the designated significance level
(α), you reject the null hypothesis. Because 0.03 < 0.05, there is sufficient statistical
evidence to reject H₀.
Question 10