https://www.stuvia.com/user/performance
WGU C207 DATA-DRIVEN DECISION MAKING: REGRESSION, PROBABILITY,
AND QUALITY TOOLS Original Questions with Answers and Rationales
Section 1: Regression Analysis (Questions)
1. What is the primary purpose of linear regression analysis?
A. To classify data into categories
B. To model the relationship between a dependent
variable and one or more independent variables
C. To sort data alphabetically
D. To clean data
Answer: B
Rationale: Linear regression models how a dependent
variable (Y) changes in response to one or more
independent variables (X), using a linear equation to
predict outcomes.
2. In the simple linear regression equation Y = b₀ + b₁X + ε,
what does ε (epsilon) represent?
A. The slope
B. The intercept
C. The error term (residual)
D. The correlation coefficient
Answer: C
Rationale: ε represents the error term—the difference
between the actual observed value and the value
,https://www.stuvia.com/user/performance
predicted by the regression line. It captures unexplained
variation.
3. What is the "least squares" method in regression analysis?
A. A method to maximize errors
B. A method that finds the line minimizing the sum of
squared residuals (errors)
C. A method to sort data
D. A method to clean data
Answer: B
Rationale: Least squares regression finds the line that
minimizes the sum of squared differences (residuals)
between observed and predicted values, producing the
best-fitting line.
4. What does the slope coefficient (b₁) in regression
represent?
A. The predicted value of Y when X equals zero
B. The average change in Y for a one-unit increase in X
C. The correlation between X and Y
D. The p-value
Answer: B
Rationale: The slope indicates how much the dependent
variable changes, on average, for each one-unit change in
the independent variable.
, https://www.stuvia.com/user/performance
5. A regression equation is Y = 10 + 2.5X. What is the
predicted value of Y when X = 4?
A. 10
B. 14
C. 20
D. 22.5
Answer: C
Rationale: Y = 10 + 2.5(4) = 10 + 10 = 20.
6. What is "multiple linear regression"?
A. Regression with one independent variable
B. Regression with two or more independent variables
predicting one dependent variable
C. Regression with two dependent variables
D. Regression without any variables
Answer: B
Rationale: Multiple regression models the relationship
between one dependent variable and several
independent variables, allowing for more complex and
realistic analysis.
7. What is "multicollinearity" in regression analysis?
A. When independent variables are highly correlated with
each other
B. When the dependent variable is correlated with
independent variables
WGU C207 DATA-DRIVEN DECISION MAKING: REGRESSION, PROBABILITY,
AND QUALITY TOOLS Original Questions with Answers and Rationales
Section 1: Regression Analysis (Questions)
1. What is the primary purpose of linear regression analysis?
A. To classify data into categories
B. To model the relationship between a dependent
variable and one or more independent variables
C. To sort data alphabetically
D. To clean data
Answer: B
Rationale: Linear regression models how a dependent
variable (Y) changes in response to one or more
independent variables (X), using a linear equation to
predict outcomes.
2. In the simple linear regression equation Y = b₀ + b₁X + ε,
what does ε (epsilon) represent?
A. The slope
B. The intercept
C. The error term (residual)
D. The correlation coefficient
Answer: C
Rationale: ε represents the error term—the difference
between the actual observed value and the value
,https://www.stuvia.com/user/performance
predicted by the regression line. It captures unexplained
variation.
3. What is the "least squares" method in regression analysis?
A. A method to maximize errors
B. A method that finds the line minimizing the sum of
squared residuals (errors)
C. A method to sort data
D. A method to clean data
Answer: B
Rationale: Least squares regression finds the line that
minimizes the sum of squared differences (residuals)
between observed and predicted values, producing the
best-fitting line.
4. What does the slope coefficient (b₁) in regression
represent?
A. The predicted value of Y when X equals zero
B. The average change in Y for a one-unit increase in X
C. The correlation between X and Y
D. The p-value
Answer: B
Rationale: The slope indicates how much the dependent
variable changes, on average, for each one-unit change in
the independent variable.
, https://www.stuvia.com/user/performance
5. A regression equation is Y = 10 + 2.5X. What is the
predicted value of Y when X = 4?
A. 10
B. 14
C. 20
D. 22.5
Answer: C
Rationale: Y = 10 + 2.5(4) = 10 + 10 = 20.
6. What is "multiple linear regression"?
A. Regression with one independent variable
B. Regression with two or more independent variables
predicting one dependent variable
C. Regression with two dependent variables
D. Regression without any variables
Answer: B
Rationale: Multiple regression models the relationship
between one dependent variable and several
independent variables, allowing for more complex and
realistic analysis.
7. What is "multicollinearity" in regression analysis?
A. When independent variables are highly correlated with
each other
B. When the dependent variable is correlated with
independent variables
