1|Page
WGU C955 MODULE 6 CORRELATION &
REGRESSION EXACT EXAM
QUESTIONS AND CORRECT ANSWERS
PLUS RATIONALES [QUESTION 1–100]
AND ANSWERS UPDATED 2026/2027 |
DETAILED RATIONALES – INSTANT
DOWNLOAD
INTRODUCTION
WGU C955 Applied Probability and Statistics Module 6: Correlation and Regression focuses on
understanding relationships between quantitative variables, interpreting scatterplots, analyzing
correlation coefficients, and using regression equations to describe and predict outcomes. These
concepts are important for students preparing for statistics assessments because they require
more than memorizing formulas: learners must interpret data, distinguish association from
causation, evaluate the strength and direction of relationships, and understand the limitations of
statistical predictions.
This practice question bank is designed for students reviewing correlation and regression
concepts through challenging, application-based scenarios. The questions cover positive and
negative relationships, Pearson's correlation coefficient, least-squares regression, slope and
intercept interpretation, residuals, outliers, influential observations, coefficient of determination,
and the appropriate use of predictions. Each question includes four answer choices, one best
answer, and a detailed rationale explaining the correct reasoning and why the alternatives are less
appropriate.
For the strongest results, attempt each problem independently before reviewing the explanation.
Pay particular attention to interpreting results in context, recognizing when extrapolation is
inappropriate, and separating statistical association from causal conclusions. This is an original
study resource, not an official WGU exam or a reproduction of actual assessment questions. Use
it alongside your course materials.
CONTENT AREA OVERVIEW
Suggested
Content area Questions Key topics
weight
Scatterplots and Direction, form, strength, outliers, visual
1–15 15%
relationships interpretation
,2|Page
Pearson's (r), magnitude, sign, limitations,
Correlation coefficient 16–30 15%
association
Least-squares line, slope, intercept,
Linear regression models 31–50 20%
prediction, interpretation
Residuals and model Residual calculations, residual plots, error
51–65 15%
evaluation patterns, fit
Coefficient of (r^2), explained variation, interpretation
66–75 10%
determination and limitations
Outliers, influence, and Influential points, linearity, extrapolation,
76–88 13%
assumptions data quality
Real-world scenarios, model selection,
Integrated applications 89–100 12%
interpretation, conclusions
The percentages are suggested study allocations for this practice set, not official WGU
assessment weights.
QUESTIONS 1–100
Section 1: Scatterplots and Relationships
Q1
A researcher records the number of hours students spend preparing for an examination and their
examination scores. The scatterplot shows that scores generally increase as study hours increase,
although the points are not perfectly aligned. Which conclusion is most appropriate?
A) The variables have a perfect positive linear relationship.
B) The variables show a positive association, but the relationship is not perfect.
C) The variables have a negative association.
D) The scatterplot proves that additional study hours cause higher scores for every student.
Rationale: B is correct because the general upward pattern indicates a positive association,
while the scattered points show that the relationship is imperfect. A is incorrect because a
perfect positive linear relationship would place all points exactly on an upward-sloping line. C
contradicts the observed direction. D makes a causal claim that a scatterplot alone cannot
establish.
Q2
,3|Page
A scatterplot of vehicle age and resale value shows that older vehicles tend to have lower resale
values. Which description best fits the pattern?
A) Positive association.
B) No association.
C) Perfect negative association.
D) Negative association.
Rationale: D is correct because resale value generally decreases as vehicle age increases. A
describes the opposite direction. B ignores the visible trend. C is too strong because the scenario
does not state that every point lies exactly on a straight line.
Q3
A researcher plots the number of hours a person exercises per week against resting heart rate.
The points form a downward-curving pattern that becomes flatter at higher exercise levels. What
is the best interpretation?
A) The relationship must be linear because the direction is negative.
B) There is no relationship because the points do not lie on a straight line.
C) The variables may have a negative nonlinear relationship, so a straight-line model may
not describe the pattern adequately.
D) The correlation coefficient must equal exactly (-1).
Rationale: C is correct because the pattern decreases but changes shape, suggesting a nonlinear
relationship. A confuses direction with form. B is incorrect because relationships need not be
linear to exist. D would require a perfect negative linear relationship, which is not indicated.
Q4
A scatterplot comparing a student's shoe size with mathematics test performance shows points
distributed without a visible trend. Which conclusion is most defensible?
A) Shoe size causes mathematics performance to vary.
B) The variables have a strong positive relationship.
C) The plot provides little visual evidence of an association between the variables.
D) The correlation coefficient must be exactly zero.
, 4|Page
Rationale: C is correct because a random-looking scatterplot provides little evidence of a clear
association. A asserts causation without evidence. B contradicts the absence of a visible upward
trend. D is too absolute: a plot may show no obvious pattern even when the calculated
correlation is small but not exactly zero.
Q5
A researcher studies advertising expenditure and sales revenue. Most points show an upward
trend, but one observation has very high advertising expenditure and unusually low sales. What
should the researcher do first?
A) Delete the observation because it weakens the relationship.
B) Replace the observation with the average sales value.
C) Investigate the observation's accuracy and context before deciding how to analyze it.
D) Assume the observation proves advertising reduces sales.
Rationale: C is correct because an unusual observation may reflect an error, a special
circumstance, or a genuine outcome. A removes data based on its effect on the result. B changes
observed data without justification. D overinterprets one point and ignores the broader pattern.
Q6
A scatterplot shows that as temperature increases, hot-drink sales decrease. The points follow a
fairly tight downward-sloping line. Which interpretation is best?
A) The relationship is positive and weak.
B) The relationship is negative and weak.
C) The relationship is positive and strong.
D) The relationship is negative and relatively strong.
Rationale: D is correct because the downward direction indicates a negative association and the
tight clustering around a line suggests relatively strong linear association. A and C describe the
wrong direction. B identifies the direction correctly but conflicts with the stated tight pattern.
Q7
A scatterplot of advertising expenditure and revenue appears curved rather than straight, with
revenue increasing rapidly at first and then leveling off. What is the most appropriate next step?
A) Use a straight-line model without examining the curvature.
WGU C955 MODULE 6 CORRELATION &
REGRESSION EXACT EXAM
QUESTIONS AND CORRECT ANSWERS
PLUS RATIONALES [QUESTION 1–100]
AND ANSWERS UPDATED 2026/2027 |
DETAILED RATIONALES – INSTANT
DOWNLOAD
INTRODUCTION
WGU C955 Applied Probability and Statistics Module 6: Correlation and Regression focuses on
understanding relationships between quantitative variables, interpreting scatterplots, analyzing
correlation coefficients, and using regression equations to describe and predict outcomes. These
concepts are important for students preparing for statistics assessments because they require
more than memorizing formulas: learners must interpret data, distinguish association from
causation, evaluate the strength and direction of relationships, and understand the limitations of
statistical predictions.
This practice question bank is designed for students reviewing correlation and regression
concepts through challenging, application-based scenarios. The questions cover positive and
negative relationships, Pearson's correlation coefficient, least-squares regression, slope and
intercept interpretation, residuals, outliers, influential observations, coefficient of determination,
and the appropriate use of predictions. Each question includes four answer choices, one best
answer, and a detailed rationale explaining the correct reasoning and why the alternatives are less
appropriate.
For the strongest results, attempt each problem independently before reviewing the explanation.
Pay particular attention to interpreting results in context, recognizing when extrapolation is
inappropriate, and separating statistical association from causal conclusions. This is an original
study resource, not an official WGU exam or a reproduction of actual assessment questions. Use
it alongside your course materials.
CONTENT AREA OVERVIEW
Suggested
Content area Questions Key topics
weight
Scatterplots and Direction, form, strength, outliers, visual
1–15 15%
relationships interpretation
,2|Page
Pearson's (r), magnitude, sign, limitations,
Correlation coefficient 16–30 15%
association
Least-squares line, slope, intercept,
Linear regression models 31–50 20%
prediction, interpretation
Residuals and model Residual calculations, residual plots, error
51–65 15%
evaluation patterns, fit
Coefficient of (r^2), explained variation, interpretation
66–75 10%
determination and limitations
Outliers, influence, and Influential points, linearity, extrapolation,
76–88 13%
assumptions data quality
Real-world scenarios, model selection,
Integrated applications 89–100 12%
interpretation, conclusions
The percentages are suggested study allocations for this practice set, not official WGU
assessment weights.
QUESTIONS 1–100
Section 1: Scatterplots and Relationships
Q1
A researcher records the number of hours students spend preparing for an examination and their
examination scores. The scatterplot shows that scores generally increase as study hours increase,
although the points are not perfectly aligned. Which conclusion is most appropriate?
A) The variables have a perfect positive linear relationship.
B) The variables show a positive association, but the relationship is not perfect.
C) The variables have a negative association.
D) The scatterplot proves that additional study hours cause higher scores for every student.
Rationale: B is correct because the general upward pattern indicates a positive association,
while the scattered points show that the relationship is imperfect. A is incorrect because a
perfect positive linear relationship would place all points exactly on an upward-sloping line. C
contradicts the observed direction. D makes a causal claim that a scatterplot alone cannot
establish.
Q2
,3|Page
A scatterplot of vehicle age and resale value shows that older vehicles tend to have lower resale
values. Which description best fits the pattern?
A) Positive association.
B) No association.
C) Perfect negative association.
D) Negative association.
Rationale: D is correct because resale value generally decreases as vehicle age increases. A
describes the opposite direction. B ignores the visible trend. C is too strong because the scenario
does not state that every point lies exactly on a straight line.
Q3
A researcher plots the number of hours a person exercises per week against resting heart rate.
The points form a downward-curving pattern that becomes flatter at higher exercise levels. What
is the best interpretation?
A) The relationship must be linear because the direction is negative.
B) There is no relationship because the points do not lie on a straight line.
C) The variables may have a negative nonlinear relationship, so a straight-line model may
not describe the pattern adequately.
D) The correlation coefficient must equal exactly (-1).
Rationale: C is correct because the pattern decreases but changes shape, suggesting a nonlinear
relationship. A confuses direction with form. B is incorrect because relationships need not be
linear to exist. D would require a perfect negative linear relationship, which is not indicated.
Q4
A scatterplot comparing a student's shoe size with mathematics test performance shows points
distributed without a visible trend. Which conclusion is most defensible?
A) Shoe size causes mathematics performance to vary.
B) The variables have a strong positive relationship.
C) The plot provides little visual evidence of an association between the variables.
D) The correlation coefficient must be exactly zero.
, 4|Page
Rationale: C is correct because a random-looking scatterplot provides little evidence of a clear
association. A asserts causation without evidence. B contradicts the absence of a visible upward
trend. D is too absolute: a plot may show no obvious pattern even when the calculated
correlation is small but not exactly zero.
Q5
A researcher studies advertising expenditure and sales revenue. Most points show an upward
trend, but one observation has very high advertising expenditure and unusually low sales. What
should the researcher do first?
A) Delete the observation because it weakens the relationship.
B) Replace the observation with the average sales value.
C) Investigate the observation's accuracy and context before deciding how to analyze it.
D) Assume the observation proves advertising reduces sales.
Rationale: C is correct because an unusual observation may reflect an error, a special
circumstance, or a genuine outcome. A removes data based on its effect on the result. B changes
observed data without justification. D overinterprets one point and ignores the broader pattern.
Q6
A scatterplot shows that as temperature increases, hot-drink sales decrease. The points follow a
fairly tight downward-sloping line. Which interpretation is best?
A) The relationship is positive and weak.
B) The relationship is negative and weak.
C) The relationship is positive and strong.
D) The relationship is negative and relatively strong.
Rationale: D is correct because the downward direction indicates a negative association and the
tight clustering around a line suggests relatively strong linear association. A and C describe the
wrong direction. B identifies the direction correctly but conflicts with the stated tight pattern.
Q7
A scatterplot of advertising expenditure and revenue appears curved rather than straight, with
revenue increasing rapidly at first and then leveling off. What is the most appropriate next step?
A) Use a straight-line model without examining the curvature.
